Open AccessArticle

The Role of Artificial Intelligence and Big Data Analytics in Shaping the Future of Professions in Industry 6.0: Perspectives from an Emerging Market

Delia Deliu

and

Andrei Olariu

Department of Accounting and Audit, Faculty of Economics and Business Administration, West University of Timişoara, RO-300115 Timişoara, Romania

Author to whom correspondence should be addressed.

Electronics 2024, 13(24), 4983; https://doi.org/10.3390/electronics13244983

Submission received: 19 November 2024 / Revised: 14 December 2024 / Accepted: 16 December 2024 / Published: 18 December 2024

(This article belongs to the Special Issue Future Trends of Artificial Intelligence (AI) and Big Data)

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Theoretical framework. "> Figure 2
Research workflow. "> Figure 3
Linear regression graph: experiences regarding the support provided by AI and BDA in performing the profession. "> Figure 4
The level of involvement of the Chamber of Financial Auditors of Romania in providing support for understanding and using AI and BDA in auditing. "> Figure 5
Respondents’ perception of the current level of professional preparedness of auditors. "> Figure 6
The most important tasks in the future considering the impact of AI and BDA. "> Figure 7
The most important skills in the context of the accelerated digitalization of the profession through AI and BDA. "> Figure 8
The extent to which the modification of International Auditing Standards is considered necessary. ">

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Abstract

Digital technologies are fundamentally transforming professions by altering roles and redefining competencies across all sectors. The progression from computerization to digitization, digitalization, and now digital transformation has been driven by the widespread integration of artificial intelligence (AI) and big data analytics (BDA). Industry 4.0 introduced smart automation and connectivity, Industry 5.0 emphasized human–machine collaboration and personalization, and Industry 6.0 now integrates advanced technologies with sustainability and ethical considerations, exerting a profound influence on many professions. This transformation is especially significant in emerging markets, where AI and BDA are overhauling traditional practices and enhancing efficiency but also introducing new challenges. Focusing on the accounting profession, this paper examines AI’s and BDA’s dual impact on the roles and skill sets of professional accountants (PAs). Specifically, it addresses how these technologies shape the activities, interactions, roles, and competencies of PAs in an Industry 6.0 context, as well as the opportunities and challenges that arise. Given the public interest role of PAs in ensuring accuracy and transparency in financial reporting, understanding their perceptions and experiences of digital transformation is essential. The findings reveal that while AI and BDA drive efficiency gains and open strategic pathways, they also risk eroding core traditional accounting competencies, reducing client engagement, and raising ethical concerns such as data security and privacy—all of which can undermine service quality and, ultimately, public trust. These insights underscore the need for responsible AI and BDA integration, particularly in emerging markets, where digital literacy gaps and regulatory limitations may slow adoption. This study offers actionable recommendations for policymakers, educators, and organizations, highlighting the importance of ethical standards, targeted training, and sustainable practices to preserve the relevance and integrity of the accounting profession in an increasingly technology-driven era.

Keywords:

digitalization; Industry 6.0; digital transformation; artificial intelligence; big data analytics; accounting; auditing; professional accountants; public interest; emerging market

1. Introduction

Digitalization has become a defining feature of modern life, fundamentally reshaping industries, sectors, and professions on a global scale. Innovations such as artificial intelligence (AI), big data analytics (BDA), cloud computing (CC), blockchain technology (BT), machine learning (ML), quantum computing (QC), augmented reality (AR), and the Industrial Internet of Things (IIoT) are driving significant advancements across domains including healthcare, security, education, media, entertainment, manufacturing, and professional services [1,2,3,4,5,6]. These technologies not only enhance productivity but also unlock new opportunities for innovation [7,8], enabling industries to address challenges that were once insurmountable.

This digital transformation is reshaping professional roles across sectors, creating a growing demand for expertise in AI integration, BDA, and technology management. For example, in the legal field, AI is leveraged to analyze extensive case law databases [9,10], while engineers utilize AI-driven digital twins to simulate complex systems and predict outcomes [11]. In the creative industries, AI assists in music composition and visual arts, blending human creativity with ML algorithms to push artistic boundaries [12]. Despite these advances, ethical concerns regarding algorithmic bias [1], data privacy, security, and the risks of excessive automation [13,14,15,16] persist. Balancing innovation with human values and equitable access has become central to the responsible use of these technologies.

The accounting profession reflects this broader trajectory of progression. Historically rooted in manual bookkeeping, the profession has steadily evolved through the eras of Industry 3.0, characterized by computerization and digitization, and Industry 4.0, defined by digitalization. More recently, Industry 5.0, through digital transformation, has introduced a focus on human–technology collaboration, setting the stage for the speculative era of Industry 6.0. These technological milestones have transitioned the profession from paper-based to electronic workflows, improving data accuracy, streamlining processes, and enhancing operational efficiency for professional accountants (PAs).

Advancements in digital technologies have brought both significant benefits and notable challenges. On one hand, the shift from manual record-keeping to digital systems has improved speed, accuracy, and regulatory compliance [17]. These advancements have enabled PAs to take on more strategic advisory roles [18,19,20,21], increasing client satisfaction. On the other hand, widespread adoption of these technologies raises concerns about job displacement and diminished human interaction between PAs and their clients [22,23,24,25,26]. Automation, while enhancing efficiency, risks diminishing human oversight [16], eroding critical judgment [27,28]. Thus, ethical questions arise around automated decision-making systems [15], particularly concerning transparency [29], fairness [30], and accountability [27]. For instance, AI-driven decision-making in environmental, social, and governance (ESG) reporting may overlook nuanced ethical considerations that require human expertise. Over-reliance on technology [15] could lead to a decline in the ability to critically assess data through professional judgment [29,31]. Ultimately, automation could diminish the advisory role of PAs, traditionally anchored in financial expertise and client interaction [16,30,32], potentially resulting in a disruption, due to the fact that the tools designed to enhance the profession inadvertently undermine essential human skills [29].

As we transition from Industry 4.0 and 5.0 to the emerging framework of Industry 6.0, digital technologies are poised to transform the business environment even further [6,33]. Industry 6.0 envisions intelligent, fully integrated systems that minimize human intervention, combining AI, human–robot collaboration, CC, BDA, and QC. These advancements will inevitably impact the accounting ecosystem. Thus, AI and BDA are already pivotal in redefining task performance and expanding the responsibilities of PAs within organizations [29,32,34]. By merging human intelligence with artificial intelligence, these technologies significantly enhance efficiency, automating repetitive tasks and reducing manual workloads [35]. This allows PAs to focus on higher-value activities such as financial analysis, strategic planning, and client advisory services [36,37,38]. The digital transformation propelled by Industry 4.0 and 5.0 principles is facilitating the evolution of PAs into strategic business advisors [39], merging technology with human expertise to drive innovation and create business value [7,40].

In Industry 6.0, the convergence of advanced technologies such as AI, robotics, and IIoT with sustainability goals [41,42,43] adds another layer of complexity as regards the balance between technological progress and sustainable development [44,45]. The accounting profession must now integrate ESG metrics into financial reporting to ensure that businesses meet sustainability targets while maintaining profitability [46]. AI and BDA empower PAs to process vast amounts of non-financial data, providing real-time insights that promote responsible business practices [47]. This transition requires interdisciplinary knowledge, including environmental science, social policy, and governance structures [41,45], underscoring the need for PAs to adapt to new skill sets.

In this context, this paper aims to examine the causal relationships between the adoption of AI and BDA and their multifaceted impacts on the accounting profession within the framework of Industry 6.0. Specifically, it investigates whether these technologies drive the evolution of the profession—broadening its scope, enhancing its relevance, and fostering strategic growth—or whether they undermine it, by eroding traditional competencies and diminishing the emphasis on human expertise. The central research question is as follows: RQ: how do AI and BDA influence the activities, interaction, roles, and skills of PAs in the context of Industry 6.0, and what opportunities and challenges do these technologies present for the profession’s future?

Empirical research is critical for understanding how PAs experience and adapt to these changes, particularly in the evolving landscape of Industry 6.0. While some professionals embrace the opportunities presented by AI and BDA—such as enhanced capabilities and new strategic roles—others may grapple with the risks of skill obsolescence, reduced client engagement, or an over-reliance on automation. Exploring these experiences provides valuable insights into the dualistic nature of technological transformation and its implications for the future of the profession. This study seeks to illuminate how PAs navigate the demands of digital transformation, offering a nuanced perspective on the evolution of their roles, skills, and core competencies in a technology-driven environment [48].

Studying the impact of digitalization on the accounting profession is especially pertinent in emerging markets such as Romania [49]. As Romania develops its digital infrastructure, the adoption of AI, BDA, and other advanced technologies presents significant opportunities for economic growth, innovation, and global competitiveness [17]. However, Romania’s relatively nascent digital economy also faces challenges, including gaps in technological adoption, digital literacy, and regulatory frameworks, which could impede the realization of these benefits [50,51]. Additionally, the rapid pace of technological change risks exacerbating job displacement and widening the skills gap, as PAs may struggle to keep up with the evolving demands of the profession [52]. Furthermore, the ethical and regulatory aspects of AI and BDA usage in Romania are still evolving. It is essential to examine how these technologies can be implemented responsibly within the accounting profession to ensure that digitalization fosters sustainable development while mitigating the risks of inequality, job loss, and ethical concerns. Thus, Romania’s experience provides a valuable perspective for other emerging markets navigating similar transitions as regards professional evolution.

First, to guide this exploration, the theoretical framework centers on the dichotomy of enhancement vs. diminishing, emphasizing the need to balance leveraging technological advancements with preserving the human competencies essential to effective accounting practice. By examining this equilibrium, this research aims to illuminate the evolving trajectory of the accounting profession in an era increasingly shaped by digital transformation, ensuring that PAs remain relevant, effective, and ethically grounded in their roles.

Second, studying PAs’ perceptions and experiences is crucial due to the significant public interest associated with the accounting profession. PAs play a vital role in ensuring the accuracy and transparency of financial reporting, thereby fostering public trust and supporting market functionality [53]. As IA and BDA reshape the required skills and competencies [54], understanding PAs’ views can reveal concerns about potential skill gaps and the loss of traditional competencies that could impact service quality. These insights can inform the development of policies and regulations to promote responsible digital practices, ensuring that ethical considerations like data privacy and the integrity of financial reporting remain central as the profession evolves. Ultimately, examining these perspectives is essential for maintaining public trust, adapting to technological advancements, and upholding the ethical standards that underpin the accounting profession.

The structure of this paper is as follows: Section 1 provides the background and context, followed by the literature review in Section 2. Section 3 details the methodology, while Section 4 presents the findings. Section 5 offers a discussion of the results. Finally, Section 6 concludes the paper with practical implications, research limitations, and suggestions for future developments.

2. Theoretical Background

This research builds on a comprehensive theoretical foundation to investigate how emerging technologies, particularly AI and BDA, are reshaping professional roles within the evolving paradigm of Industry 6.0. By integrating key concepts and relevant studies, this section provides the context needed to frame the study’s hypothesis and theoretical framework. The exploration is structured to address three central themes. First, the transformative concept of Industry 6.0 is explored, focusing on its implications for professional roles, particularly within the accounting field. Second, the impact of AI and BDA on the accounting profession is examined, highlighting emerging trends and challenges in this rapidly evolving landscape. Lastly, the dual impact of these technologies is analyzed through a theoretical framework that identifies both the opportunities for innovation and efficiency and the potential risks associated with the over-reliance on technology and the erosion of critical human competencies. This exploration not only underscores the relevance of AI and BDA within the Industry 6.0 framework but also lays the groundwork for the methodological and empirical analyses that follow, providing a structured approach to understanding the accounting profession’s evolution amid digital transformation.

2.1. The Emergence of Industry 6.0: Redefining Professional Roles and Responsibilities

Industry 6.0 marks a transformative phase in industrial evolution, characterized by the seamless integration of advanced digital technologies with a heightened focus on sustainability, ethics, and human-centered design [41]. Building upon its predecessors—Industry 4.0 and Industry 5.0—this phase represents the next step in technological advancement. Industry 4.0 emphasized automation, connectivity, and smart systems powered by the IoT and BDA. Industry 5.0, by contrast, introduced a human-centric shift, focusing on collaboration between humans and machines, personalization, well-being, and ethical considerations. Industry 6.0 expands these principles by envisioning a future where technology complements human capabilities rather than replaces them [39]. This approach fosters collaboration between human workers and machines, enhancing productivity [45] while addressing ethical concerns surrounding automation.

The defining features of Industry 6.0 include the convergence of advanced technologies, such as AI, ML, BT, and AR. These technologies enable real-time data analysis and informed decision-making [43], paving the way for more agile and responsive business models [42]. Organizations that successfully adopt these advancements can optimize operations, enhance customer experiences, and drive innovation, securing a competitive advantage in an increasingly dynamic market landscape.

The impact of Industry 6.0 extends beyond industries to professions, including accounting. PAs must adapt to the rapid technological changes and evolving market demands brought about by this transformative phase. Industry 6.0 prioritizes human expertise in areas requiring judgment, creativity, and ethical reasoning, ensuring that the role of PAs remains indispensable in maintaining trust and accountability.

The integration of digital technologies demands a shift in the skill sets required for PAs. To remain relevant, PAs must develop advanced technical competencies, particularly in data analysis, cybersecurity, and the ethical application of AI. This evolution challenges traditional training and education programs, necessitating a re-evaluation of curriculum to prepare future PAs for the demands of Industry 6.0. As routine tasks become increasingly automated, PAs are positioned to focus on higher-value activities such as strategic decision-making, guiding digital transformation initiatives, and addressing complex ethical dilemmas arising from technological advancements. Consequently, the scope of the PA’s role expands beyond traditional compliance and financial reporting, requiring interdisciplinary expertise that integrates technology, governance, and sustainability [46].

Moreover, the hallmark of Industry 6.0 is its emphasis on interdisciplinary collaboration [41,42,43]. PAs will increasingly work alongside IT specialists, data analysts, and sustainability experts to tackle multifaceted challenges. This collaborative approach enhances problem-solving capabilities and equips organizations to navigate the complexities of a human-centric, sustainable, and technologically integrated business environment. For PAs operating in emerging markets, this transformation requires agility and adaptability, as accounting firms, particularly SMEs, undergo significant digital transformation in response to Industry 6.0.

As AI and BDA become central to decision-making processes in Industry 6.0, the ethical implications of their use must not be overlooked. These technologies rely on human-designed algorithms, which inherently carry biases and limitations. To harness their full potential for societal benefit, it is critical to embed ethical principles in their design, training, and implementation [1]. Key concerns, such as human autonomy, privacy, equality, and social justice, must be prioritized to mitigate the moral risks posed by technological interventions [29,55]. For PAs, ensuring transparency and accountability in these systems is crucial, as their professional decisions have significant consequences for individuals, organizations, and society at large.

2.2. The Impact of AI and BA in Accounting: Future Trends in the Context of Industry 6.0

Digital technologies are reshaping professional landscapes across sectors, fostering efficiency and innovation. In the accounting profession, AI and BDA are redefining roles and competencies. Previous studies highlight that these advancements streamline processes and enhance accuracy and service quality, allowing PAs to transition into strategic advisory positions [18,19]. However, this transformation also raises critical concerns regarding job displacement and the potential erosion of traditional skills.

One of the most significant advancements is the integration of AI, which automates routine tasks such as data entry, reconciliation, and report generation. AI-driven tools like ML and optical character recognition (AI-OCR) are automating repetitive tasks such as data extraction from financial documents, enhancing the speed and accuracy of financial document processing [56]. This automation not only saves time, improving efficiency, but also reduces the likelihood of human error, improving accuracy [57] and allowing PAs to focus on higher-value activities such as financial analysis and strategic advisory services [58]. AI’s capabilities in machine learning and predictive analytics enable PAs to derive insights from data that were previously unattainable, thereby enhancing decision-making and strategic planning.

BDA further complements AI by providing tools to analyze vast amounts of financial and non-financial data. BD techniques provide advanced decision-making capabilities, predictive analysis, and risk management, which are crucial for modern accounting practices [56,59]. These technologies enable PAs to handle both structured and unstructured data effectively [57], enhancing their role in data-driven decision-making [60], and ultimately complementing their existing skills [54]. PAs can now sift through extensive datasets to identify trends, assess risks, and forecast financial performance with greater precision. This ability to leverage data-driven insights positions PAs as vital strategic partners within their organizations, as they contribute to informed decision-making and enhanced operational efficiency. The literature indicates that the effective use of BDA can lead to improved performance outcomes and a deeper understanding of client needs, allowing PAs to tailor their services more effectively [29,34].

However, the adoption of these advancements is not without challenges. As the landscape of accounting evolves, PAs must develop new competencies to effectively navigate this digital transformation. This includes not only technical skills in data analytics and technology management but also soft skills such as critical thinking and communication to engage with clients and stakeholders. The shift toward a technology-driven accounting environment necessitates a re-evaluation of traditional accounting roles and responsibilities, pushing PAs to adapt and evolve in order to remain relevant and effective in their profession.

Consequently, digital technologies are fundamentally reshaping accounting practices, driving both operational efficiency and strategic innovation. The integration of AI and BDA not only enhances the accuracy and timeliness of financial reporting but also necessitates the development of new skills and competencies among PAs. As the profession continues to embrace these technological advancements, understanding their implications and the evolving role of PAs will be essential for sustaining the profession’s relevance in an increasingly digital world.

2.3. Theoretical Framework: Navigating the Positive and Negative Impacts of AI and BDA on the Accounting Profession Amid Digital Transformation

This study’s theoretical framework revolves around the positive and negative impacts of AI and BDA on the accounting profession. The framework offers a structured way to analyze how these technological advancements reshape the roles, responsibilities, and skills of PAs, especially in the context of Industry 6.0.

First, we depict the positive transformation of professional roles, enhanced by technological integration. As AI becomes embedded in accounting processes, routine tasks are automated, allowing PAs to focus on higher-value activities such as financial forecasting, strategic advisory services, and business analysis. This shift not only improves productivity but elevates PAs’ strategic roles within organizations. Emerging technologies like BDA further drive this evolution by empowering PAs to analyze vast datasets and extract actionable insights, thus moving beyond traditional roles to participate in more data-driven decision-making processes. As real-time data become increasingly crucial, PAs are encouraged to continuously develop new skills, particularly in data analytics and technology management.

On the other hand, a more cautionary scenario suggests that while digital tools may improve efficiency, they could also undermine essential human skills. Research warns of a potential over-reliance on technology, leading to the erosion of core competencies such as critical thinking, professional judgment, and interpersonal communication. As tasks become more automated, PAs may become distanced from the detailed understanding of financial transactions, risking the profession’s depth and ethical integrity. Research suggests that this reliance on automation could diminish PAs’ decision-making capabilities in complex situations, where human input and ethical considerations are crucial. In this sense, while technology enhances operational aspects, the profession must ensure that critical skills remain intact and not lost to automation [15].

Table 1 provides a detailed, multifaceted examination of the contrasting pathways that digital transformation could carve within the accounting profession, encapsulated through the lenses of the positive and negative implications of AI and BDA. This is explored in terms of their unique impacts on core areas such as professional roles, skills development, technology adoption, client engagement, and ethical considerations, each critical in shaping the profession’s future.

Table 1 highlights that AI and BDA can foster both opportunities and risks. While digital transformation offers an optimistic path of enhanced capabilities and strategic relevance, it also must warn as regards skill atrophy and weakened professional influence. The accounting profession is thus at a crossroads, where the potential for growth and innovation exists alongside the risks of diminished human expertise and reduced accountability. Scholars advocate for a balanced approach, urging PAs to not only embrace technological changes but also reinforce their core skills [104].

3. Related Work

Research on digital transformation in Romania has been conducted across various sectors and groups, but it primarily focuses on professionals other than PAs. For example, one study investigated Romanian managers’ perceptions and personal experiences as regards Industry 4.0 processes, showing that factors such as perceived competitiveness and perceived risk significantly influence their intention to adopt these processes [105]. It also emphasized the positive impact of vertical networking and integrated engineering solutions on managers’ intentions to use Industry 4.0 technologies, illustrating how digital transformation fosters competitiveness and operational efficiency. Another study examined the experiences of professionals, executives, and managers from local and multinational companies in Romania [106], focusing on the challenges and practical benefits of digital transformation in the context of sustainability strategies. While this research provided valuable insights into how digital transformation is reshaping businesses, it did not specifically address the accounting profession. In the financial sector, a study assessed the extent of digitalization in Romanian banking [107], offering a detailed analysis of its integration and highlighting the sector’s long-term viability in the digital era. Although it provided significant insights into banking practices, their focus on sector-specific trends limits its applicability to broader professional competencies. On a more individual level, another research study explored digital transformation acceptance among Romanian individuals [108], emphasizing that behavioral and innovative characteristics strongly influence attitudes toward digitalization. The findings demonstrated a positive impact of these attitudes on both personal and social acceptance of digital technologies.

These studies collectively underscore a growing interest in the implications of digital transformation in Romania. While existing research provided valuable insights into how digital transformation is reshaping businesses in Romania, most of them did not specifically address how specific professions, such as accounting, are adapting to and integrating digital transformation, highlighting a critical gap that this study seeks to address. Thus, the accounting profession—particularly the perceptions and experiences of PAs—remains underexplored, highlighting the contribution of the present study.

Recent research focusing on Romanian PAs has begun to shed light on the significant opportunities and challenges posed by digital transformation. One study examined the pressures faced by PAs in North-Eastern Europe, including Romania, and highlighted how the rapid acceleration of digitalization, coupled with overlapping crises, has compelled the profession to adopt innovative measures [109]. It identified several factors influencing PAs’ readiness for further training, including the perceived ease of using digital tools, performance levels achieved, expected effort, and situational factors such as organizational culture and regulatory policies. It also noted concerns about job security due to AI replacing human roles, as well as risks associated with data loss and errors in reporting. Another study explored the digital transformation frontiers of managerial accounting through the lens of cyber accounting [110] revealing how digital tools can enhance organizational performance. By examining the economic implications of digitalization, it provided a managerial perspective on how digital transformation shapes accounting decisions and strategies, offering valuable insights for Romanian PAs. In a similar vein, a bibliometric analysis of the intersection of internet-related technologies and accounting offered a global overview of the literature [111], showcasing the evolution of debates in the field and identifying future thematic directions. For Romanian PAs, all these findings offered a pathway to aligning their practices with the broader global trends while addressing local challenges. Moreover, research also highlights the paradigm shift in the accounting profession in Romania, documenting the evolving role of PAs from transaction loggers to strategic analysts and consultants [112]. This shift emphasizes how digitalization has moved from being a modern solution driven by technological progress to a necessity, particularly in light of the unpredictable economic and social conditions caused by the COVID-19 pandemic. This transition underscores the growing importance of PAs as strategic advisors and the imperative for them to adopt digital tools to meet evolving demands.

Together, these studies provide a valuable foundation for understanding the impact of digital transformation on Romanian PAs, emphasizing the profession’s evolution in response to technological advancements and societal changes. However, while these works explore critical aspects of the accounting profession in Romania, they do not specifically examine the perceptions and experiences of PAs regarding AI and BDA within the broader context of Industry 6.0. Addressing this gap forms the basis of the present study, which aims to provide actionable insights into how Romanian PAs perceive and adapt to these technologies.

Parallel studies further underline a paradigm shift in Romanian accounting, where practitioners transition from conventional systems to digital workflows. These studies advocate for upskilling as essential to maintaining service quality, enhancing management decision-making, and supporting business sustainability in a digitalized world [50,94].

In this context, it is important to note that existing research also highlights the transformative impact of digitalization on Romanian accounting practices and education, particularly emphasizing the role of universities in bridging traditional accounting methodologies with digital competencies. For instance, universities are pivotal in equipping future professionals with essential skills, preparing them to lead in a rapidly evolving technological environment [17]. However, this body of work largely focuses on educational institutions’ preparatory roles and overlooks the practices and perceptions of current professionals actively navigating digital transformation. While aligned with the global trends emphasizing digital literacy and analytics, the existing research does not delve into how these changes redefine professional identities or the integration of advanced tools like AI and BDA into accounting practices in emerging contexts, leaving room for deeper exploration.

Globally, AI and BDA are recognized as transformative forces, enabling cost optimization, real-time data integration, and strategic decision-making. Romanian research indicates these technologies are beginning to influence management accounting practices. For example, studies document how AI and BDA drive innovation in resource-constrained contexts while highlighting enablers like targeted training and organizational adaptability [51]. However, challenges such as gaps in digital literacy, limited access to advanced technologies, and misalignment with global standards persist. Tailored approaches are needed to address these issues, particularly in emerging markets like Romania.

Efforts by professional bodies such as the Chamber of Financial Auditors of Romania (CAFR) and the Body of Expert and Licensed Accountants of Romania (CECCAR) to integrate digital competencies into training reflect a growing commitment to addressing these challenges [50,51]. Yet, progress remains incremental, with persistent barriers to technology access and training resources. This divergence from global best practices further highlights the need for sustained investment in digital transformation initiatives to support lifelong learning and ensure PAs maintain their expertise and professional judgment.

While global trends in AI and BDA adoption emphasize structured frameworks for technology integration, Romania’s approach appears to be incremental and adaptive to local conditions. On the one hand, as regards global practices, countries with advanced accounting ecosystems prioritize national frameworks for digital transformation, often in partnership with technology firms. These initiatives provide practitioners with hands-on experience in cutting-edge tools and methodologies. On the other hand, the Romanian context is different. In Romania, efforts remain focused on foundational digital literacy and integrating AI and BDA within existing professional standards, with universities and professional bodies playing a pivotal role in driving these changes. However, gaps in access to technology and training resources persist [50,51]. Consequently, this commitment to lifelong learning and professional development ensures that PAs can navigate the complexities of digital transformation without sacrificing their fundamental expertise and ultimately, their professional judgment [113].

This study adds a distinct contribution by exploring the experiences of Romanian PAs on the dual impact of AI and BDA, addressing a gap in understanding how these professionals view and adapt to Industry 6.0 demands. Unlike existing studies, which tend to generalize the challenges of digital transformation, our research focuses on capturing the nuanced experiences of PAs in Romania, offering insights into how local constraints shape digital transformation practices.

The present study situates itself within this body of literature by addressing several gaps. First, with regard to perceptions and experiences in adoption, existing research often examines digital transformation from an organizational or systemic perspective but seldom focuses on the experiences of individual practitioners, particularly in emerging markets like Romania. Second, concerning contextual nuances, while global frameworks for AI and BDA integration provide valuable benchmarks, their application in resource-constrained settings remains underexplored. This study provides a localized perspective, shedding light on how PAs navigate these challenges while aligning with Industry 6.0 demands. Third, concerning future competencies, by emphasizing the intersection of sustainability, innovation, and technology, our research highlights the emergence of new roles and competencies within the accounting profession, which go beyond traditional practices.

By analyzing data gathered through questionnaires distributed to CAFR members, this study offers a comprehensive understanding of the digital transformation of accounting in Romania. The findings will reveal how PAs perceive and adopt AI and BDA, identifying both opportunities (e.g., enhanced decision-making, real-time data analysis) and challenges (e.g., skill gaps, ethical considerations). These insights will contribute to the broader discourse on aligning local practices with global digital transformation trends while addressing Romania’s unique economic and professional context.

In contrast to incremental improvements, the transformation driven by AI and BDA signals a fundamental restructuring of the accounting profession. New paradigms, such as sustainability accounting, ethical data governance, and real-time analytics, redefine professional competencies and roles. By exploring the perceptions and experiences of Romanian PAs, this study bridges a critical gap in the literature, offering actionable insights for policymakers, educators, and practitioners aiming to align with Industry 6.0 demands.

By situating the current study within this body of literature, we address a critical gap: existing research, while offering valuable insights into education and practice, does not comprehensively examine the experiences of PAs regarding digital transformation in emerging markets, particularly in the context of Industry 6.0. This study contributes new knowledge by exploring how PAs perceive the dual impact of AI and BDA, identifying both opportunities and challenges, and providing actionable insights that align with global digital transformation trends while addressing Romania’s unique context as an emerging market.

4. Materials and Methods

This study adopts a structured methodological approach to examine the influence of digital technologies, particularly AI and BDA, on the accounting profession within the context of an emerging market. By focusing on Romanian auditors, the research situates global technological advancements within a specific national and professional framework, capturing both broader trends and localized insights. The approach combines exploratory analysis with empirical investigation, ensuring that the methods align with the study’s objectives while providing a strong foundation for examining the dual impact of these technologies. The research process commenced with the development of a theoretical framework (Figure 1), which informed the creation of a targeted questionnaire.

To ensure the reliability and clarity of the instrument, a pilot test (pre-test) was conducted, through interviews, with 10 experienced auditors who are also members of academia. This dual expertise provided valuable feedback, as the participants brought both practical insights from the field and theoretical perspectives from their academic background. Feedback from the pilot test was used to refine the questionnaire, addressing ambiguities and ensuring the questions were aligned with the research objectives. This iterative process enhanced the validity of the data collection tool and ensured its suitability for capturing relevant responses from a broader sample [114]. The pilot test played a critical role in ensuring the methodological rigor of this study, contributing to the reliability and relevance of the findings.

Following the refinement, the questionnaire was distributed to a selected sample of PAs. Responses were analyzed using statistical methods to test the study’s hypotheses and uncover significant patterns.

4.1. Research Hypotheses

The profession now faces a pivotal moment where traditional functions are being replaced or augmented by advanced systems, necessitating adaptation to maintain relevance and integrity.

This leads to the central research hypothesis of the paper:

H1:

The adoption of artificial intelligence (AI) and big data analytics (BDA) by professional accountants (PAs) causes significant changes in their activities and roles within organizations.

This hypothesis arises from the understanding that while AI and BDA provide greater efficiency, accuracy, and access to real-time data, they also introduce challenges that compel PAs to adjust their approaches to professional tasks (Figure 1). These technologies, though beneficial, demand the acquisition of new technical skills and bring potential shifts in traditional practices that have long defined the field.

Building on this overarching hypothesis, four operational sub-hypotheses emerge, reflecting different dimensions of the transformation, and further examining the multifaceted impact of AI and BDA:

H1a:

The adoption of artificial intelligence (AI) and big data analytics (BDA) drives professional accountants (PAs) to acquire new skills and take on expanded responsibilities, thereby enhancing their professional capabilities.

This hypothesis examines whether the integration of AI and BDA serves as a catalyst for upskilling and broadening professional competencies. It underscores the critical need for ongoing skill development and highlights how these technologies expand the scope of expertise within the accounting profession.

H1b:

The adoption of artificial intelligence (AI) and big data analytics (BDA) facilitates a shift in professional accountants’ (PAs) roles from traditional compliance-based tasks to more strategic and analytical functions.

This hypothesis tests whether the integration of AI and BDA causally drives role evolution within the profession. It reflects the profession’s transformation toward higher-value activities, enabled by automation and advanced analytics.

H1c:

Increased reliance on artificial intelligence (AI) and big data analytics (BDA) negatively impacts traditional accounting skills, as the automation of routine tasks leads to their gradual erosion.

This hypothesis explores whether automation reduces the relevance of foundational accounting expertise over time. It considers the potential risk of skill degradation caused by over-reliance on technology, which could undermine the core technical capabilities of the profession.

H1d:

The integration of artificial intelligence (AI) and big data analytics (BDA) diminishes the frequency and depth of professional accountants’ (PAs) direct client interactions, as automated systems increasingly manage communication and reporting processes.

This hypothesis investigates the causal relationship between AI/BDA integration and changes in client engagement dynamics. It raises concerns about preserving the human element, a traditionally central component of client relationships in accounting services.

Together, these sub-hypotheses provide a structured framework for exploring the complex and dualistic effects of AI and BDA on the accounting profession. They offer insights into opportunities for growth and innovation, while also addressing the challenges that demand thoughtful and strategic navigation to preserve the profession’s core values and competencies.

4.2. Research Approach

This study is part of a broader research initiative examining the impact of digitalization on the accounting profession, with a particular emphasis on emerging economies. Employing an exploratory research design combined with empirical analysis, the present study investigates how digital technologies—specifically AI and BDA—are reshaping the roles and perceptions of accounting practitioners. By centering on the perspectives of Romanian auditors, the research seeks to offer critical insights into the technological transformations affecting their profession, while also addressing the challenges and opportunities these changes present.

To achieve this, the research follows a systematic workflow divided into seven key stages to ensure a comprehensive and structured approach (Figure 2). The research process is initiated with the definition of objectives and research questions, which sets the foundation for this study by clarifying its goals and scope. The second stage, documentation, involved a thorough review of the specialized literature to identify relevant sources and construct the theoretical framework. In the third stage, questionnaire design, a data collection instrument is developed, with a focus on the validity and relevance of the questions to ensure relevant findings. The fourth stage focuses on questionnaire distribution, leveraging the internal communication channels of CAFR to reach a representative sample of auditors. In the fifth stage, response collection, efforts are made to ensure that the gathered data are accurate, complete, and reflective of the target population. The sixth stage involves statistical analysis, where SPSS is used to process and interpret the responses, deriving meaningful insights from the data. Finally, the seventh stage focuses on drafting conclusions, synthesizing the findings into actionable recommendations that address the study’s objectives and provide a roadmap for future exploration.

4.3. Data Collection and Sample Size

The data collection targeted Romanian chartered certified auditors who are members of the Chamber of Financial Auditors of Romania (CAFR). An online questionnaire was developed to align with the study’s objectives and hypotheses regarding the influence of AI and BDA on the profession. The questionnaire was distributed through CAFR’s internal communication channels, ensuring targeted delivery and high response rates. This direct approach allowed for the efficient collection of high-quality data from a relevant professional audience.

To establish a representative sample, official CAFR records were consulted, and a population of 222 registered members was identified based on criteria pertinent to this study. This ensured that the statistical population was appropriately aligned with the research objectives.

The minimum response threshold needed to validate the questionnaire and achieve statistical relevance was calculated (Table 2). A total of 119 responses were received, of which 1 was excluded due to invalidity, leaving 118 valid responses. The final sample exceeded the required threshold of 117 valid responses, as determined by a 94% confidence level and a 6% margin of error, strengthening the reliability and representativeness of the findings (Table 3).

4.4. Validity and Reliability

The validity of the questionnaire was assessed through criterion validity and coherence [115]. These constructs ensured that the questionnaire effectively measured its intended outcomes and aligned with the study’s objectives. It included questions on demographics (e.g., age, gender, and professional experience) as well as respondents’ perceptions and personal experiences on digitalization and the role of AI and BDA in professional activities. Additional questions explored the initial impressions of digital tools, the perceived importance of digital transformation, and the anticipated challenges and opportunities for the accounting profession.

To provide a broader perspective, the questionnaire also examined the role of professional bodies such as CAFR in facilitating digitalization. The questions addressed the perceived need for updates to the International Auditing Standards to keep pace with technological advancements. Correlations between demographic factors, professional experience, and experiences on digitalization were analyzed to uncover relationships. For example, gender and age were linked to experience in using digital tools, while professional experience was compared with attitudes toward AI and BDA.

Reliability, a crucial aspect of ensuring stable and consistent results [116], was achieved by employing purposive sampling rather than random sampling. Participants were specifically selected based on their active engagement in financial and statutory audits during 2022, ensuring their insights reflected relevant and current practices [117]. This approach was particularly important given the significant workplace transformations caused by the COVID-19 pandemic, including the shift to remote work [118], platform-based operations [119], and the increased reliance on digital tools [54]. By targeting PAs with direct experience in these changes, this study ensured the data captured real-world practices influenced by digital transformation.

Romania’s status as a dynamic emerging market provided a valuable context for this study. The country’s ongoing digital transformation and transitioning economy offered a unique opportunity to examine how AI and BDA are reshaping accounting and auditing practices. The questionnaire was designed to reflect these dynamics, focusing on the specific challenges and opportunities faced by Romanian auditors. By incorporating local professional experiences and aligning with CAFR’s strategic initiatives, this study delivers practical insights into the profession’s adaptation to digitalization.

CAFR’s involvement was instrumental in facilitating the research. As the primary authority for auditors in Romania, CAFR supported the distribution of the questionnaire and played a key role in addressing the challenges regarding the digitalization of the accounting profession. Its efforts include organizing training programs, issuing updated technology guidelines, and collaborating with international organizations to align Romanian standards with global advancements. These initiatives were embedded in the questionnaire design, ensuring its relevance to the current context of the profession.

The reliability of the questionnaire was further supported by the careful selection of participants with extensive expertise in external auditing. Each respondent brought direct, practical experience with financial and statutory audits during a period of significant digital change. This targeted sampling guaranteed that the collected data reflected informed perspectives from PAs actively navigating the challenges of digital transformation from Industry 5.0 to Industry 6.0.

4.5. Questionnaire Design

The questionnaire was designed to obtain relevant responses on how AI and BDA influence accounting practices. It consisted of 27 questions, structured to collect both categorical and scaled data. The design included a mix of single-choice, multiple-choice, and Likert-scale questions to provide respondents with flexibility while ensuring coverage of the research theme. Thus, our questionnaire employed a Likert-scale format for most of the questions, ranging from 1 to 5, where 1 indicated “strongly disagree” or “very low”, and 5 indicated “strongly agree” or “very high”. This approach was chosen to capture nuanced responses [120] and provide insights into participants’ experiences on using AI and BDA in the accounting activities. For questions requiring categorical data, multiple-choice options were used to classify responses by demographic factors, professional experience, perceptions of digitalization, and experiences on the adoption of digital tools.

The first section collected demographic information, such as professional background, years of experience, and familiarity with digital technologies. These demographic data were essential for understanding how individual factors influence experiences as regards the digital transformation of the profession. The second section focused on the core research themes, addressing how AI and BDA affect professional practices, the challenges of integrating these technologies, and the role of professional bodies like CAFR in facilitating digital transformation. The interconnected structure of the questions allowed for the identification of patterns in the data, providing nuanced insights into the respondents’ experiences.

The questionnaire’s design allowed for the cross-validation of responses, further enhancing its credibility. For instance, participants’ views on the importance of digitalization were corroborated by their reported use of advanced digital tools in their work. Similarly, their opinions on institutional support aligned with their involvement in CAFR-led initiatives, reflecting a comprehensive understanding of the challenges and opportunities in their field.

Consequently, this study achieves more than data collection; it establishes trust in its findings. The results are not only relevant but also transformative, ultimately offering a clear roadmap for how emerging markets can leverage digitalization—in general, and AI and BDA—in particular to reshape professional practices.

4.6. Data Analysis

The questionnaire responses were analyzed using the IBM SPSS Statistics 30.0.0 software [121,122], employing a range of statistical methods to test the study’s hypothesis. Univariate analyses, including frequency tables and graphical representations, summarized response distributions, providing an overview of the data. Bivariate analyses examined relationships between variables, such as age, gender, and professional experience, in relation to experiences in using AI and BDA.

Linear regression analysis (LRA) was used to explore correlations [123] between independent variables—such as the level of interest in digitalization, perceived technological transformation, and the role of AI and BDA—and the dependent variable, which was the perceived support provided by AI and BDA in professional tasks. The regression model quantified these relationships, offering insights into the strength and accuracy of the associations.

Additionally, an analysis of variance (ANOVA) test was conducted to compare group variances [124] and identify significant differences in perceptions and experiences as regards digital technology support across demographic and professional categories.

5. Results

The results of this study provide a comprehensive examination of how digital technologies, particularly AI and BDA, are influencing various dimensions of the accounting profession within the context of Romania. This section systematically presents the findings through a series of detailed analyses, beginning with cross-tabulations to explore relationships between demographic factors such as gender, age, and professional experience and their impact on perceptions of digitalization. Additionally, key variables such as the use of AI and BDA tools, interest in digital transformation, and preparedness for adopting these technologies are analyzed to uncover patterns and trends. The results also include regression analyses to identify the factors driving digital transformation and their implications for the profession. Insights are further enriched by exploring the role of professional bodies in supporting digital adoption, evaluating professional preparedness for digital transformation, and examining how generational perspectives shape views on the future of accounting. The analysis highlights the tasks and skills likely to gain importance in the future and underscores the need for adapting International Standards to align with the evolving digital landscape. Together, these findings provide valuable insights into the opportunities and challenges posed by digital transformation in accounting, with a particular focus on emerging markets.

Gender and age distribution

The analysis explored the relationship between respondents’ gender and other factors such as age and professional experience. Table 4 highlights that 25.42% of the 118 participants are female (30 respondents), while 74.58% are male (88 respondents). Regarding the age distribution, 4.24% are aged 25–30, 23.73% fall within 30–45, 67.80% are aged 46–60, and 4.24% are over 60 years old. Age is considered an important variable, as it contributes to diverse perspectives and experiences that, combined with gender, offer a more nuanced understanding of attitudes and behaviors within the profession.

Gender and professional experience

Table 5 illustrates the differences in professional experience between male and female respondents. Among male participants, 2.27% have 2–5 years of experience, 9.09% have 5–10 years, 12.50% have 10–20 years, and 76.14% have over 20 years of experience. In contrast, 10% of female respondents have 5–10 years of experience, 6.67% have 10–20 years, and 83.33% have over 20 years of experience in financial auditing. These variations highlight gender-specific trends in experience levels and provide a detailed understanding of expertise across the field.

Initial experiences in using BDA tools and AI technology and perception of the importance of digitalization

Table 6 examines the relationship between respondents’ use of BDA tools and AI technology, their initial impressions of these advancements, and their perception of digitalization’s importance. Among the respondents, 73 (61.9%) reported using AI and BDA in their work, while 45 (38.1%) stated they did not. A majority (72.8%) of users described their initial interaction with digital tools as complicated but manageable over time, while 71.2% of users considered digitalization “very important”, compared to 51.1% among non-users. These findings indicate a positive correlation between the adoption of AI and BDA and the recognition of their importance for professional activities.

Age and perceptions of BDA tools and AI technology

Table 7 presents the relationship between age groups and initial experiences in using AI and BDA. Among respondents aged 25–30, 40% found the tools intuitive, while 60% described them as initially complicated but manageable. In the 30–45 age group, 64.3% found their first interactions challenging but improved with practice, and 28.6% required specialist assistance. The 46–60 age group showed a similar trend, with 77.5% initially struggling but adapting, while 22.5% needed ongoing support. Respondents over 60 found the interaction complicated, with 60% requiring time to adapt and 40% needing specialized assistance. These findings suggest that experience in using AI and BDA vary significantly across age groups, with younger respondents showing greater adaptability.

Interest in digitalization and professional development

Table 8 explores the perceived importance of digitalization and respondents’ level of interest in adopting these technologies. A significant majority (83.05%) expressed high interest in the digital transformation of their workplace. These results align with the hypotheses that PAs recognize the critical role of digitalization in transforming their work. Moreover, 115 out of 118 respondents agreed that AI and BDA significantly enhance efficiency and effectiveness in professional tasks, underscoring the perceived benefits of these tools in practice.

Interest in digitalization and technological support

Table 9 examines the relationship between PAs’ interest in the digitalization of the accounting profession and their experiences regarding the support provided by AI and BDA in daily work tasks. This analysis highlights how interest in digital transformation aligns with the perceived benefits of these technologies, offering insights into areas where digital tools may need enhancement to increase engagement and improve work efficiency. The majority of respondents (115 out of 118) acknowledged that AI and BDA significantly enhance the efficiency and effectiveness of professional activities. In contrast, only three respondents felt that these technologies do not provide meaningful support. Among those with a high interest in digitalization, the perception of AI and BDA as effective tools was particularly pronounced, underscoring a strong connection between enthusiasm for digital transformation and positive evaluations of its impact.

Preparedness for AI and BDA

Table 10 examines the link between respondents’ preparedness to use digital technologies and their interest in digitalization. Among respondents, 113 (95.76%) felt adequately prepared to use AI and BDA, while 5 (4.24%) did not. Those who felt prepared also exhibited higher levels of interest in digitalization, indicating a strong association between readiness and enthusiasm for adopting these technologies. This suggests that improved training and support could further foster interest and engagement in digital transformation initiatives.

Perception of digitalization and the future of the profession

Table 11 highlights the relationship between interest in digitalization and perceptions of the profession’s future. Of the respondents with a high level of interest, 98 believed that AI and BDA would positively shape the profession, enhancing its efficiency and relevance. In contrast, five respondents with moderate interest perceived digitalization as a factor that could redefine the accounting profession, potentially leading to significant changes in roles and responsibilities. These findings reflect varying levels of optimism about the profession’s future and suggest that greater support and communication may help address uncertainties regarding technological advancements.

Generational perspectives on the future of accounting profession

Table 12 explores the relationship between age groups and perceptions of the accounting profession’s future in light of digitalization. By comparing responses across age demographics, the analysis sheds light on generational differences in attitudes toward the role of AI and BDA in shaping the field. Respondents aged 46–60 were most likely to view digitalization as a redefinition of the accounting profession, with five participants in this group emphasizing the transformative potential of these technologies. Meanwhile, the overwhelming majority of respondents (113 out of 118), spanning all age groups, perceived AI and BDA as a favorable influence that supports professional progress. This broad consensus reflects strong confidence in the ability of AI and BDA to enhance the field’s effectiveness and relevance.

Regression analysis of digital transformation factors

The multiple linear regression analysis presented in Table 13, Table 14 and Table 15 and Figure 3 explored the relationships between three key factors and professionals’ experiences with technological support. These factors include the following: interest in digitalization, the perceived transformative impact of technologies, and the role of digital tools such as AI and BDA. The results revealed statistically significant correlations among these variables, with p-values of 0.013, 0.025, and <0.001, respectively. The Pearson correlation coefficient was 0.597, indicating a moderate positive relationship between the independent variables and the dependent variable, which reflects experiences with technological support.

The model’s representativeness was confirmed by an ANOVA F statistic of 20.998 and a significance level of <0.001, suggesting that the regression model is robust and meaningful. Moreover, the R-Square value of 0.356 indicates that 35.6% of the variation in technological support experiences can be explained by the combined influence of these three factors. However, the remaining 64.4% of the variation points to the presence of additional influences, highlighting the multifaceted nature of digital transformation in the accounting profession.

This analysis underscores the moderate but significant impact of digital transformation drivers while also emphasizing the need for further research into other potential contributors to the diverse experiences professionals have with technological tools.

Insights from statistical analysis

Table 16 provides a descriptive statistical analysis examining the key factors, including experiences with AI and BDA support, interest in digitalization, and perceptions of the transformative impact of these technologies on the profession.

The analysis revealed that an overwhelming majority of respondents (115 out of 118) agreed that AI and BDA significantly enhance efficiency and effectiveness in professional tasks, underscoring their pivotal role in optimizing processes. In contrast, a small minority (three respondents) perceived the impact of these technologies as minimal, highlighting divergent views on their transformative potential.

When considering the broader impact of AI and BDA, 15 respondents (12.7%) stated that these tools have fundamentally redefined the profession. The remaining participants acknowledged their influence as substantial but not revolutionary. This suggests a nuanced understanding of the role these technologies play, with most respondents recognizing them as essential drivers of change.

Additionally, there was a broad consensus regarding the importance of digitalization, with the majority viewing it as a critical factor in the profession’s ability to adapt and thrive in a technology-driven landscape. These findings reflect a shared confidence in the profession’s readiness to embrace digital transformation and capitalize on emerging technological advancements.

Role of professional bodies in supporting digitalization of the profession in an emerging market

The involvement of professional organizations, particularly the Chamber of Financial Auditors of Romania (CAFR), was a key focus of this analysis. As Figure 4 illustrates, 61% of respondents rated CAFR’s support for digital transformation as highly significant, while 30% noted a moderate level of involvement. Only 9% perceived minimal support, highlighting room for further efforts by professional bodies to bridge gaps in digital readiness.

CAFR’s initiatives, including training programs, technology updates, and collaborations with global organizations, are seen as critical to equipping auditors with the skills needed to integrate AI and BDA into their practices. For instance, on 25 August 2024, CAFR launched the Romanian version of the Digital Competence Maturity Model, a tool that helps small- and medium-sized accounting and auditing firms to evaluate and improve digital skills [125]. The DCMM questionnaire identifies the current level of digitization and sets clear directions for the development of the digital skills necessary to adapt to new technologies [126]. These types of measures not only enhance the efficiency of auditing tasks but also ensure alignment with evolving global standards, strengthening the competitiveness of Romanian auditors in the international context.

Professional preparedness for digital transformation

Assessing the level of professional training of auditors becomes an essential component in understanding how they are prepared to respond to the challenges and opportunities brought by AI and BDA. Figure 5 shows that the majority of auditors are relatively well-prepared professionally in the context of these evolving digital technologies. However, there are varying opinions regarding the level of preparedness, and this diversity of perceptions and experiences highlights the importance of continuing professional development to ensure the proper approach to technological challenges.

Future tasks and skill requirements

Figure 6 identifies the tasks that PAs expect to become increasingly important in the digital era. The most frequently mentioned priority, with 106 responses, was automating routine activities to allocate more time for decision-making and strategic analysis. Other tasks, such as updating work procedures and improving forecasting capabilities, received comparatively fewer mentions, suggesting a clear focus on leveraging technology to enhance decision-making processes.

Figure 7 highlights the skills deemed essential for adapting to digital transformation. A significant majority (109 respondents) emphasized the importance of understanding and using AI and BDA, reflecting the profession’s growing reliance on technical competencies. Risk detection and management skills were also highlighted, albeit to a lesser extent, while client communication skills received relatively low priority, indicating a shift in focus toward technical and analytical expertise.

Adapting International Standards to digital transformation

As digital tools reshape auditing practices, respondents highlighted the need for updates to International Standards on Auditing (ISA). Figure 8 reveals diverse opinions: 42 respondents supported significant changes to address technological advancements, while 31 advocated for extensive revisions. Conversely, a smaller group (12 respondents) suggested only slight modifications, and 3 felt the current standards remain adequate. These findings underscore the importance of ongoing dialogue to ensure that auditing standards remain relevant in a rapidly evolving digital landscape.

In conclusion, our findings provide an understanding of how digital transformation, driven by AI and BDA, is reshaping the accounting profession in an emerging market like Romania, characterized by resistance to change and high volatility.

6. Discussion

The findings validate the central hypothesis and its sub-hypotheses, confirming that PAs perceive AI and BDA as having a significant impact on their activities and roles within organizations. A strong consensus emerged among respondents, with the majority recognizing the transformative potential of these technologies in enhancing efficiency, effectiveness, and task execution. However, demographic factors such as age, gender, and professional experience influence perceptions and readiness for digitalization, highlighting the need for tailored strategies, particularly in emerging markets like Romania. This mirrors global patterns, where regional disparities in technological infrastructure and professional preparedness shape the adoption of digital transformation [127].

Respondents expressed significant interest in digitalization, with a clear recognition of the role of AI and BDA in reshaping traditional accounting models. The perceived benefits of these technologies, such as process optimization [18,19,20,21], and improved decision-making [29,43] were central to the positive attitudes toward digital transformation. However, while the overall sentiment was optimistic, this study identified gaps in training and professional development [54,69], particularly in equipping professionals with the necessary digital tools and aligning existing professional standards with these technological advancements. Professional bodies, such as CAFR in Romania, play a pivotal role in addressing these challenges by offering targeted training and guidance. Similar trends are observed globally, where institutions such as AICPA and ICAEW provide continuous learning opportunities to bridge skill gaps and promote digital proficiency [128]. While there is broad agreement that AI and BDA significantly improve accounting practices, some respondents argue that more support from professional bodies is needed to address the rapid pace of digital transformation. This indicates that, despite the general positive attitude, there is a recognition that more initiatives are required to fully integrate these technologies into daily practice.

The impact of AI and BDA on accounting is dual-faceted. On one hand, these technologies enhance professional capabilities and expand responsibilities [59,71,72,73]. On the other hand, there are concerns about skills erosion [54,69] and reduced human interaction [32,91,92,93]. The findings indicate that, while most respondents acknowledge the positive impact on efficiency [34,35,57], there is some divergence in opinion about how these technologies may negatively change professional roles [60,61,78,79] in the long term. This variation is particularly noticeable in emerging markets, where challenges such as limited technological infrastructure and resources may hinder the adoption of advanced tools [58]. Globally, advanced economies mitigate these risks through robust training programs and ethical frameworks [127], whereas emerging markets, including Romania, face challenges in addressing digital literacy gaps and resource constraints [50,51].

The ethical and compliance dimensions of AI and BDA integration emerged as critical concerns, consistent with international research. Issues such as data privacy, security, and algorithmic bias [7,32,96,97,98,99,100] demand urgent attention. Romanian respondents emphasized the need to adapt International Auditing Standards to address these risks, reflecting similar global calls for evolving ethical guidelines by IFAC and other organizations [128]. This demonstrates a universal recognition of the need to ensure the accountability and integrity of the accounting profession amidst digital transformation.

The disparity between large firms and smaller practices in adopting digital technologies is another significant finding. Larger firms leverage greater resources to seamlessly integrate AI and BDA [127], while smaller firms struggle due to financial and infrastructural limitations. This trend is evident in Romania, where resource-constrained firms face hurdles in keeping pace with technological advancements [17,94]. Addressing these disparities requires targeted interventions, such as subsidized training programs and access to affordable tools, to ensure equitable progress across the industry.

Lastly, the findings emphasize the importance of continued professional development [34,57,61]. PAs must acquire skills in data science, analytics, and cybersecurity [69] to remain competitive. While large firms are likely to benefit more from technological advancements, smaller firms, particularly in emerging markets like Romania, may face difficulties in keeping pace, potentially creating a divide in the industry’s technological capabilities.

In this context, training and professional development are critical for ensuring the sustainability of the accounting profession, particularly in emerging markets like Romania. Globally, universities and professional bodies are already integrating AI and BDA into their curricula, emphasizing interdisciplinary programs that combine data analytics with traditional accounting practices [127,128]. In Romania, institutions are aligning training programs with industry demands [17,50,51,94], but gaps remain in bridging academic preparation with practical needs. Collaboration between academia, industry, and professional organizations is crucial to closing these gaps and equipping future PAs with both technical and ethical competencies.

While this study provides valuable insights, it is not without limitations. The sample size, focused on Romanian PAs, may limit the generalizability of the findings to other regions. Additionally, the reliance on self-reported data introduces potential biases. This study also focused on perceptions and initial experiences rather than the actual impact of AI and BDA on daily tasks, leaving room for future research to explore real-world implications. Broader organizational factors, such as leadership and culture, were not examined but are likely to play significant roles in facilitating digital transformation.

Accordingly, future research should expand on these findings by including a diverse sample of PAs from various regions to allow for comparative analyses. Longitudinal studies could track the adoption of AI and BDA over time, while case studies could provide deeper insights into their practical application. Developing frameworks for the ethical and responsible use of these technologies will also be crucial, ensuring that their integration enhances public trust and accountability in the accounting profession. By addressing these areas, future research can further illuminate the transformative potential of AI and BDA, particularly within the evolving framework of Industry 6.0.

As the accounting profession stands at the threshold of this technological revolution, it is clear that AI and BDA are not just reshaping tasks but redefining the essence of professional roles. This evolution, however, requires a delicate balance between innovation and responsibility. The integration of these technologies must be approached thoughtfully, ensuring that their benefits are harnessed ethically, inclusively, and sustainably. The future of accounting, being a public interest profession, lies not only in embracing change but in navigating it with integrity, foresight, and a commitment to both professional development and societal well-being. It is in this context that we must now turn to the final reflections on the implications of these findings and their potential to drive the profession forward.

7. Conclusions

This study set out to investigate the dual impact of AI and BDA on the accounting profession within the evolving framework of Industry 6.0. Specifically, it explored whether the integration of these technologies enhances the profession by expanding its scope and significance or diminishes it by eroding traditional competencies and reducing the emphasis on human expertise. The central hypothesis that PAs perceive AI and BDA to have a significant impact on their roles was supported by the findings.

AI and BDA are shown to drive substantial transformations in the accounting profession, reshaping it to align with the demands of Industry 6.0. These technologies enable the automation of routine tasks, enhance decision-making processes, and allow practitioners to assume more strategic roles within organizations. This is particularly significant in emerging markets such as Romania, where digital infrastructure and adoption are still evolving. AI and BDA hold promise for elevating the accounting profession, fostering innovation, and aligning with sustainability and ethical goals. However, these advancements also bring challenges, including potential skill atrophy, over-reliance on automation, and ethical dilemmas, which may compromise the human-centric aspects of the profession.

This study makes several significant contributions to the understanding of digital transformation in accounting. First, it provides empirical evidence of the challenges and opportunities posed by AI and BDA, particularly in emerging markets like Romania, which are navigating the complexities of digital adoption. Second, it highlights the importance of professional bodies such as the Chamber of Financial Auditors of Romania (CAFR) in supporting PAs through this transition. CAFR’s role in offering training programs, updating auditing standards, and aligning with global practices underscores the need for institutional support in managing technological shifts. Third, this study presents a dual-impact theoretical framework for analyzing the benefits and risks of integrating AI and BDA, offering a structured approach to understanding how these technologies influence the accounting profession. Lastly, it provides policy recommendations emphasizing the need for robust ethical guidelines and updated regulatory frameworks to ensure the responsible use of advanced technologies in accounting.

The findings of this study have significant practical implications for various stakeholders. For practitioners, the results underscore the necessity of continuous professional development to build technical and strategic skills while safeguarding traditional competencies such as critical judgment and ethical reasoning. These insights stress the importance of lifelong learning to adapt to evolving technological demands. For regulators and policymakers, this study highlights the urgency of revising auditing and accounting standards to incorporate the realities of a digital-first profession. Updated frameworks must address ethical concerns such as data privacy, transparency, and fairness to maintain public trust in the profession. Academia, educators, and training institutions are also key stakeholders in this transformation. This study underscores the need for curriculum reforms that prepare future PAs to navigate interdisciplinary challenges. These reforms should integrate technological, governance, and sustainability training to ensure that future professionals are equipped to handle the multifaceted demands of Industry 6.0.

Given the pace of technological advancements, this study points to several avenues for future research. Longitudinal studies could provide insights into how the accounting profession evolves over time with the continued adoption of AI and BDA. These studies could track changes in skills, competencies, and professional roles, offering a dynamic understanding of digital transformation. Qualitative research could complement the quantitative findings of this study by delving deeper into PAs’ experiences with digital technologies. Interviews and case studies could uncover nuanced perspectives on challenges, opportunities, and the human impact of these transformations. Additionally, comparative analyses across regions and sectors could identify universal trends and region-specific challenges in digital transformation, contributing to a global understanding of these phenomena. Finally, research on the impact of digitalization on smaller firms and less experienced auditors could address existing gaps by exploring how these groups navigate the adoption of AI and BDA and what tailored support they may require.

In conclusion, the integration of AI and BDA presents both substantial opportunities and significant challenges for the accounting profession. These technologies have the potential to elevate the profession by fostering innovation, enhancing efficiency, and enabling strategic roles. However, their successful adoption depends on achieving a careful balance between leveraging technological advancements and preserving the essential human expertise that defines the field.

Professional bodies, educators, and policymakers must collaborate to support PAs through this transition. By fostering continuous professional development, updating regulatory standards, and prioritizing ethics, stakeholders can ensure that the accounting profession remains resilient and impactful in the face of digital transformation. As Industry 6.0 continues to evolve, ongoing research and proactive adaptation will be essential for maintaining public trust and ensuring that the profession thrives in the Digital Age. Through these efforts, the accounting profession can navigate the complexities of technological change while safeguarding its core values and responsibilities.

Author Contributions

Conceptualization, D.D. and A.O.; methodology, A.O.; software, A.O.; validation, D.D. and A.O.; formal analysis, D.D.; investigation, D.D.; resources, A.O.; data curation, A.O.; writing—original draft preparation, A.O.; writing—review and editing, D.D.; visualization, D.D. and A.O.; supervision, D.D.; project administration, D.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

Ntoutsi, E.; Fafalios, P.; Gadiraju, U.; Iosifidis, V.; Nejdl, W.; Vidal, M.E.; Ruggieri, S.; Turini, F.; Papadopoulos, S.; Krasanakis, E.; et al. Bias in data-driven artificial intelligence systems—An introductory survey. Wiley Interdiscip. Rev. Data Min. Knowl. Discov. 2020, 10, e1356. [Google Scholar] [CrossRef]
Amato, G.; Carrara, F.; Ciampi, L.; Di Benedetto, M.; Gennaro, C.; Falchi, F.; Messina, N.; Vairo, C. AI and computer vision for smart cities. In Proceedings of the 8th Italian Conference on ICT for Smart Cities and Communities, Ascoli Piceno, Italy, 14–16 September 2022; University of Camerino: Ascoli Piceno, Italy, 2022. [Google Scholar]
Tzionis, G.; Antzoulatos, G.; Papaioannou, P.; Mavropoulos, A.; Gialampoukidis, L.; Burgos, M.G.; Vrochidis, S.; Kompatsiaris, I.; Vlachopoulou, M. Evaluation of Explainable Artificial Intelligence Methods in Language Learning Classification of Spanish Tertiary Education Students. In Interactive Mobile Communication & Artificial Intelligence, 15th ed.; Auer, M.E., Tsiatsos, T., Eds.; Springer Nature: Cham, Switzerland, 2023; pp. 351–362. [Google Scholar]
Karakostas, A.; Vrochidis, S.; Kompatsiaris, I. Using Artificial Intelligence to Manage Extreme Weather Events: The Impact of the beAWARE Solution. In Responding to Extreme Weather Events, 1st ed.; Sempere-Torres, D., Karakostas, A., Rossi, C., Quevauviller, P., Eds.; John Wiley & Sons Ltd.: Hoboken, NJ, USA, 2024; pp. 181–198. [Google Scholar]
Papadimitriou, I.; Gialampoukidis, I.; Vrochidis, S.; Kompatsiaris, I. AI methods in materials design, discovery and manufacturing: A review. Comput. Mater. Sci. 2024, 235, 112793. [Google Scholar] [CrossRef]
Manta, A.G.; Bădîrcea, R.M.; Doran, N.M.; Badareu, G.; Gherțescu, C.; Popescu, J. Industry 4.0 Transformation: Analysing the Impact of Artificial Intelligence on the Banking Sector through Bibliometric Trends. Electronics 2024, 13, 1693. [Google Scholar] [CrossRef]
Mancini, D.; Lamboglia, R.; Castellano, N.G.; Corsi, K. Trends of digital innovation applied to accounting information and management control systems. In Reshaping Accounting and Management Control Systems—New Opportunities from Business Information Systems; Corsi, K., Castellano, N.G., Lamboglia, R., Mancini, D., Eds.; Springer: Cham, Switzerland, 2017; pp. 1–19. [Google Scholar]
Ebirim, G.U.; Unigwe, I.F.; Oshioste, E.E.; Ndubuisi, N.L.; Odonkor, B.; Asuzu, O.F. Innovations in accounting and auditing: A comprehensive review of current trends and their impact on U.S. businesses. Int. J. Sci. Res. 2024, 11, 965–974. [Google Scholar]
Cijan, A.; Jenič, A.; Lamovsek, A.; Stemberger, J. How Digitalization Changes the Workplace. Dyn. Relatsh. Manag. J. 2019, 8, 3–21. [Google Scholar] [CrossRef]
Kraus, S.; Ferraris, A.; Bertello, A. The future of work: How innovation and digitalization re-shape the workplace. J. Innov. Knowl. 2023, 8, 100438. [Google Scholar] [CrossRef]
Attaran, M.; Celik, B.G. Digital Twin: Benefits, use cases, challenges, and opportunities. Decis. Anal. J. 2023, 6, 100165. [Google Scholar] [CrossRef]
Pattanaik, S.; Mohammed, M.; Sood, V. Artificial intelligence and machine learning in Industry 6.0. In Industry 6.0.: Technology, Practices, Challenges, and Applications, 1st ed.; Reddy, C.K.K., Doss, S., Pamulaparty, L., Lippert, K., Doshi, R., Eds.; CRC Press: Boca Raton, FL, USA, 2024; pp. 37–54. [Google Scholar]
Holt, M.; Lang, B.; Sutton, S.G. Potential employees’ ethical perceptions of active monitoring: The dark side of data analytics. J. Inf. Syst. 2017, 31, 107–124. [Google Scholar] [CrossRef]
Martin, K. Ethical implications and accountability of algorithms. J. Bus. Ethics 2019, 160, 835–850. [Google Scholar] [CrossRef]
Shaw, J. Artificial Intelligence and ethics: Ethics and the dawn of decision-making machines. Harvard 2019, 30, 1–11. [Google Scholar]
Seethamraju, R.; Hecimovic, A. Adoption of artificial intelligence in auditing: An exploratory study. Aust. J. Manag. 2022, 48, 780–800. [Google Scholar] [CrossRef]
Guşe, G.R.; Mangiuc, M.D. Digital transformation in Romanian accounting practice and education: Impact and perspectives. Amfiteatru Econ. 2022, 24, 252–267. [Google Scholar] [CrossRef]
Andreassen, R.I. Digital technology and changing roles: A management accountant’s dream or nightmare? J. Manag. Control 2020, 31, 209–238. [Google Scholar] [CrossRef]
Barth, M.E.; Li, K.; McClure, C.G. Evolution in Value Relevance of Accounting Information. Account. Rev. 2022, 98, 1–28. [Google Scholar] [CrossRef]
Farhan, K.A.; Kawther, B.I. Accounting audit profession in digital transformation environment between theoretical framework and practical reality. World Econ. Financ. Bull. 2023, 22, 120–123. [Google Scholar]
Jackson, D.; Michelson, G.; Munir, R. Developing accountants for the future: New technology, skills, and the role of stakeholders. Account. Educ. 2023, 32, 150–177. [Google Scholar] [CrossRef]
Imene, F.; Imhanzenobe, J. Information technology and the accountant today: What has really changed? J. Account. Taxation 2020, 12, 48–60. [Google Scholar]
Spilnyk, I.; Brukhanskyi, R.; Struk, N.; Kolesnikova, O.; Sokolenko, L. Digital accounting: Innovative technologies cause a new paradigm. Indep. J. Manag. Prod. 2022, 13, 215–224. [Google Scholar] [CrossRef]
Taib, A.; Awang, Y.; Shuhidan, S.M.; Rashid, N.; Hasan, M.S. Digitalization in Accounting: Technology Knowledge and Readiness of Future Accountants. Univers. J. Account. Financ. 2022, 10, 348–357. [Google Scholar] [CrossRef]
Afsay, A.; Tahriri, A.; Rezaee, Z. A meta-analysis of factors affecting acceptance of information technology in auditing. Int. J. Account. Inf. Syst. 2023, 49, 100608. [Google Scholar] [CrossRef]
Yigitbasioglu, O.; Green, P.; Cheung, M.D. Digital transformation and accountants as advisors. Account. Audit. Account. J. 2023, 36, 209–237. [Google Scholar] [CrossRef]
Gunz, S.; Thorne, L. Thematic symposium: The impact of technology on ethics, professionalism and judgement in accounting. J. Bus. Ethics 2020, 167, 153–155. [Google Scholar] [CrossRef]
Gordon, D.; Stavrakakis, I.; Gibson, J.P.; Tierney, B.; Becevel, A.; Curley, A.; Collins, M.; O’Mahony, W.; O’Sullivan, D. Perspectives on computing ethics: A multi-stakeholder analysis. J. Inf. Commun. Ethics Soc. 2022, 20, 72–90. [Google Scholar] [CrossRef]
Tiron-Tudor, A.; Rodgers, W.; Deliu, D. The accounting profession in the Twilight Zone: Navigating digitalisation’s sided challenges through ethical pathways for decision-making. Account. Audit. Account. J. 2024. ahead-of-print. [Google Scholar]
Alles, M.; Munoko, I.; Vasarhelyi, M. Ethics and the future of artificial intelligence in auditing. In Artificial Intelligence in Accounting. Organisational and Ethical Implications, 1st ed.; Lehner, O.M., Knoll, C., Eds.; Routledge: London, UK, 2022; pp. 217–231. [Google Scholar]
Commerford, B.P.; Dennis, S.A.; Joe, J.R.; Ulla, J.W. Man versus machine: Complex estimates and auditor reliance on artificial intelligence. J. Account. Res. 2022, 60, 171–201. [Google Scholar] [CrossRef]
Quattrone, P. Management accounting goes digital: Will the move make it wiser. Manage. Account. Res. 2016, 31, 118–122. [Google Scholar] [CrossRef]
Poláková, M.; Suleimanová, J.H.; Madzík, P.; Copuš, L.; Molnárová, I.; Polednová, J. Soft skills and their importance in the labour market under the conditions of Industry 5.0. Heliyon 2023, 9, e18670. [Google Scholar] [CrossRef] [PubMed]
Zhang, C.; Zhu, W.; Dai, J.; Wu, Y.; Chen, X. Ethical impact of artificial intelligence in managerial accounting. Int. J. Account. Inf. Syst. 2023, 49, 100619. [Google Scholar] [CrossRef]
Arnaboldi, M.; Busco, C.; Cuganesan, S. Accounting, accountability, social media, and big data: Revolution or hype. Account. Audit. Account. J. 2017, 30, 762–776. [Google Scholar] [CrossRef]
Greenman, C. Exploring the impact of artificial intelligence on the accounting profession. J. Res. Bus. Econ. Manag. 2017, 8, 1451. [Google Scholar]
Janssen, M.; Hartog, M.; Matheus, R.; Yi Ding, A.; Kuk, G. Will algorithms blind people? The effect of explainable AI and decision-makers’ experience on AI-supported decision-making in government. Soc. Sci. Comput. Rev. 2022, 40, 478–493. [Google Scholar] [CrossRef]
Kokina, J.; Davenport, T.H. The emergence of artificial intelligence: How automation is changing auditing. J. Emerg. Technol. Account. 2017, 14, 115–122. [Google Scholar] [CrossRef]
Tiron-Tudor, A.; Deliu, D. Reflections on the human-algorithm complex duality perspectives in the auditing process. Qual. Res. Account. Manag. 2022, 19, 255–285. [Google Scholar]
Deliu, D. Professional Judgment and Skepticism Amidst the Interaction of Artificial Intelligence and Human Intelligence. Audit. Financ. J. 2024, 22, 724–741. [Google Scholar] [CrossRef]
Chourasia, S.; Tyagi, A.; Pandey, S.M.; Walia, R.S.; Murtaza, Q. Sustainability of Industry 6.0 in global perspective: Benefits and challenges. MAPAN-J. Metrol. Soc. India 2022, 37, 443–452. [Google Scholar] [CrossRef]
Srivastava, A.; Kumari, G.; Pathania, A. Technological Innovation and Accounting in Industry 6.0: Application, Implication, and Future. In Sustainable Innovation for Industry 6.0; Sharma, A., Moses, O., Sharma, R.B., Gupta, S., Eds.; IGI Global: Hershey, PA, USA, 2024; pp. 286–309. [Google Scholar]
Vijay, A.J.; William, B.N.J.; Haruna, A.A.; Prasad, D.D. Exploring the synergy of IIoT, AI, and data analytics in Industry 6.0. In Industry 6.0: Technology, Practices, Challenges, and Applications, 1st ed.; Reddy, C.K.K., Doss, S., Pamulaparty, L., Lippert, K., Doshi, R., Eds.; CRC Press: Boca Raton, FL, USA, 2024; pp. 1–36. [Google Scholar]
Annanperä, E.; Jurmu, M.; Kaivo-oja, J.; Kettunen, P.; Knudsen, M.; Lauraéus, T.; Majava, J.; Porras, J. From Industry x to Industry 6.0: Antifragile Manufacturing for People, Planet, and Profit With Passion; White Paper—Business Finland; Allied ICT Finland (AIF): Oulu, Finland, 2021. [Google Scholar]
Almusaed, A.; Yitmen, I.; Almssad, A. Reviewing and integrating aec practices into industry 6.0: Strategies for smart and sustainable future-built environments. Sustainability 2023, 15, 13464. [Google Scholar] [CrossRef]
Salin, A.S.A.P.; Hasan, H.C.; Kamarudin, N.N.A.N.; Mad, S. Formulating A Competency Framework for Accountants on Environment, Social and Governance (ESG) Standards and Finance Digitalization. Inf. Manag. Bus. Rev. 2024, 16, 309–317. [Google Scholar] [CrossRef]
Petcu, M.A.; Sobolevschi-David, M.I.; Curea, S.C. Integrating digital technologies in sustainability accounting and reporting: Perceptions of professional cloud computing users. Electronics 2024, 13, 2684. [Google Scholar] [CrossRef]
Orlikowski, W.J.; Iacono, C.S. Research commentary: Desperately seeking the “IT” in IT research—A call to theorizing the IT artifact. Inf. Syst. Res. 2001, 12, 121–134. [Google Scholar] [CrossRef]
Ionescu-Feleagă, L.; Dragomir, V.D.; Bunea, Ș.; Stoica, O.C.; Barna, L.-E.-L. Empirical Evidence on the Development and Digitalization of the Accounting and Finance Profession in Europe. Electronics 2022, 11, 3970. [Google Scholar] [CrossRef]
Socoliuc, M.I. The Impact of Digitalization on the Accounting Profession in Romania–A Quantitative Research. Rev. Stud. Financ. 2023, 8, 132–154. [Google Scholar] [CrossRef]
Pantea, M.F.; Cilan, T.F.; Cuc, L.D.; Rad, D.; Bâtcă-Dumitru, G.C.; Șendroiu, C.; Almași, R.C.; Feher, A.; Gomoi, B.C. Optimizing Romanian Managerial Accounting Practices through Digital Technologies: A Resource-Based and Technology-Deterministic Approach to Sustainable Accounting. Electronics 2024, 13, 3206. [Google Scholar] [CrossRef]
Bobitan, N.; Dumitrescu, D.; Popa, A.F.; Sahlian, D.N.; Turlea, I.C. Shaping Tomorrow: Anticipating Skills Requirements Based on the Integration of Artificial Intelligence in Business Organizations—A Foresight Analysis Using the Scenario Method. Electronics 2024, 13, 2198. [Google Scholar] [CrossRef]
Berdiyarovich, B.S. The Role of Accounting and Auditing in Ensuring Financial Transparency. Econ. Innov. 2024, 46, 91–98. [Google Scholar]
Tiron-Tudor, A.; Deliu, D. Big data’s disruptive effect on job profiles: Management accountants’ case study. J. Risk Financ. Manag. 2021, 14, 376. [Google Scholar] [CrossRef]
Knudsen, D.-R. Elusive boundaries, power relations, and knowledge production: A systematic review of the literature on digitalisation in accounting. Int. J. Account. Inf. Syst. 2020, 36, 1–22. [Google Scholar] [CrossRef]
Malladhi, A. Automating financial document processing: The role of AI-OCR and big data in accounting. Int. Res. J. Modernization Eng. Technol. Sci. 2023, 5, 4628–4638. [Google Scholar]
Moll, J.; Yigitbasioglu, O. The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. Br. Account. Rev. 2019, 51, 100833. [Google Scholar] [CrossRef]
Holmes, A.F.; Douglass, A. Artificial intelligence: Reshaping the accounting profession and the disruption to accounting education. J. Emerg. Technol. Account. 2022, 19, 53–68. [Google Scholar] [CrossRef]
Chu, M.K.; Yong, K.O. Big data analytics for business intelligence in accounting and audit. Open J. Soc. Sci. 2021, 9, 42–52. [Google Scholar] [CrossRef]
Richins, G.; Stapleton, A.; Stratopoulos, T.C.; Wong, C. Big data analytics: Opportunity or threat for the accounting profession? J. Inf. Syst. 2017, 31, 63–79. [Google Scholar] [CrossRef]
Lehner, O.M.; Ittonen, K.; Silvola, H.; Ström, E.; Wuhrleitner, A. Artificial intelligence based decision-making in accounting and auditing: Ethical challenges and normative thinking. Account. Audit. Account. J. 2022, 35, 109–135. [Google Scholar] [CrossRef]
Bras, J.C.; Pereira, R.F.; Fonseca, M.; Ribeiro, R.; Bianchi, I.S. Advances in auditing and business continuity: A study in financial companies. J. Open Innov. Technol. Mark. Complex. 2024, 10, 100304. [Google Scholar] [CrossRef]
Medida, L.H.; Kumar, G.L.N.V.s. Addressing Challenges in Data Analytics: A Comprehensive Review and Proposed Solutions. In Critical Approaches to Data Engineering Systems and Analysis Book, 1st ed.; Bora, A., Changma, P., Maharana, M., Eds.; IGI Global: New York, NY, USA, 2024; pp. 16–33. [Google Scholar]
Onyshchenko, O.; Shevchuk, K.; Shara, Y.; Koval, N.; Demchuk, O. Industry 4.0 and Accounting: Directions, Challenges, Opportunities. Indep. J. Manag. Prod. 2022, 13, 161–195. [Google Scholar] [CrossRef]
Ibrahim, A.; Elamer, A.A.; Ezat, A.N. The convergence of big data and accounting: Innovative research opportunities. Technol. Forecast. Soc. Chang. 2021, 173, 121171. [Google Scholar] [CrossRef]
Arnold, V.; Sutton, S.G. The theory of technology domi-nance: Understanding the impact of intelligent decision aids on decision maker’s judgments. Adv. Account. Behav. Res. 1998, 1, 175–194. [Google Scholar]
Theodorakopoulos, L.; Thanasas, G.; Halkiopoulos, C. Implications of Big Data in Accounting: Challenges and Opportunities. Emerg. Sci. J. 2024, 8, 1201–1214. [Google Scholar] [CrossRef]
Herath, S.K.; Woods, D. Impacts of big data on accounting. Bus. Manag. Rev. 2021, 12, 195–203. [Google Scholar] [CrossRef]
Eisikovits, N.; Johnson, W.C.; Markelevich, A. Should Accountants Be Afraid of AI? Risks and Opportunities of Incorporating Artificial Intelligence into Accounting and Auditing. Account. Horiz. 2024, 1–7. [Google Scholar] [CrossRef]
Al Lawat, H.; Sanad, Z.; Al Farsi, M. Unveiling the Influence of Big Data Disclosure on Audit Quality: Evidence from Omani Financial Firms. Adm. Sci. 2024, 14, 216. [Google Scholar] [CrossRef]
Akhter, A.; Sultana, R. Sustainability of accounting profession at the age of fourth industrial revolution. Int. J. Account. Financ. Rep. 2018, 8, 139. [Google Scholar] [CrossRef]
Maulidiya, S.; Nurdin, A.; Rohmadani, F.; Pandin, M.Y.R. The Role of Digital Accountant 5.0 Towards the Accountant Profession. J. Riset Inov. Manaj. 2023, 1, 360–372. [Google Scholar]
Zhang, Y.; Xiong, F.; Xie, Y.; Fan, X.; Gu, H. The impact of artificial intelligence and blockchain on the accounting profession. IEEE Access 2020, 8, 110461–110477. [Google Scholar] [CrossRef]
Ghani, E.K.; Muhammad, K. Industry 4.0: Employers’ Expectations of Accounting Graduates and Its Implications on Teaching and Learning Practices. Int. J. Educ. Pract. 2019, 7, 19–29. [Google Scholar] [CrossRef]
Jarosz, S.; Sołtysik, M.; Zakrzewska, M. The Fourth Industrial Revolution in the Light of Social and Competence Changes. Eur. Res. Stud. 2020, 23, 530–548. [Google Scholar] [CrossRef]
Villa, J.V.; Sharairi, M.H.; Navarrete, A.C.; Sancho, G.F.I. An accounting information systems perspective on data analytics and big data during 2015–2020. Turk. J. Comput. Math. Educ. 2021, 12, 509–514. [Google Scholar]
Nwaimo, C.S.; Adegbola, A.E.; Adegbola, M.D.; Adeusi, K.B. Evaluating the role of big data analytics in enhancing accuracy and efficiency in accounting: A critical review. Fin. Account. Res. J. 2024, 6, 877–892. [Google Scholar] [CrossRef]
Munoko, I.; Brown-Liburd, H.; Vasarhelyi, M.A. The Ethical Implications of Using Artificial Intelligence in Auditing. J. Bus. Ethics 2020, 167, 209–234. [Google Scholar] [CrossRef]
Rikala, P.; Braun, G.; Järvinen, M.; Stahre, J.; Hämäläinen, R. Understanding and measuring skill gaps in Industry 4.0—A review. Technol. Forecast. Soc. Chang. 2024, 201, 123206. [Google Scholar] [CrossRef]
Haryanto, S.D.; Sudaryati, E. The Ethical Perspective of Millennial Accountants in Responding to Opportunities and Challenges of Blockchain 4.0. J. Account. Invest. 2020, 21, 452–470. [Google Scholar] [CrossRef]
Imjai, N.; Swatdikun, T.; Rungruang, P.; Basiruddin, R.; Aujirapongpan, S. Empowering generation z accountants in the era of data complexity and open innovation: Nurturing big data analytics, diagnostic, and forensic accounting skills. J. Open Innov. Technol. Mark. Complex 2024, 10, 100308. [Google Scholar] [CrossRef]
Zhong, H.; Yang, D.; Shi, S.; Wei, L.; Wang, Y. From data to insights: The application and challenges of knowledge graphs in intelligent audit. J. Cloud Comput.-Adv. Syst. Appl. 2024, 13, 114. [Google Scholar] [CrossRef]
Munevar, K.; Patatoukas, P.N. The Blockchain Evolution and Revolution of Accounting. In Information for Efficient Decision Making: Big Data, Blockchain and Relevance; World Scientific: Singapore, 2020; pp. 1–21. [Google Scholar]
Antwi, B.O.; Adelakun, B.O.; Eziefule, A.O. Transforming Financial Reporting with AI: Enhancing Accuracy and Timeliness. Int. J. Adv. Econ. 2024, 6, 205–223. [Google Scholar] [CrossRef]
Oyeniyi, L.D.; Ugochukwu, C.E.; Mhlongo, N.Z. Transforming Financial Reporting with AI: Enhancing Accuracy and Timeliness. Financ. Account. Res. J. 2024, 6, 626–647. [Google Scholar]
Estep, C.; Griffith, E.E.; MacKenzie, N.L. How do financial executives respond to the use of artificial intelligence in financial reporting and auditing? Rev. Account. Stud. 2024, 29, 2798–2831. [Google Scholar] [CrossRef]
Hamdam, A.; Jusoh, R.; Yajya, Y.; Jalil, A.; Abidin, N.H.Z. Auditor judgment and decision-making in big data environment: A proposed research framework. Account. Res. J. 2021, 35, 55–70. [Google Scholar] [CrossRef]
Han, H.; Shiwakoti, R.K.; Jarvis, R.; Mordi, C.; Botchie, D. Accounting and auditing with blockchain technology and artificial Intelligence: A literature review. Int. J. Account. Inf. Syst. 2023, 48, 100598. [Google Scholar] [CrossRef]
Dagilienė, L.; Klovienė, L. Motivation to use big data and big data analytics in external auditing. Manag. Audit. J. 2019, 34, 750–782. [Google Scholar] [CrossRef]
Nwekwo, N.M.; Agbo, B.O.; Echefu, S.C. The data-driven accountant: Leveraging data analytics for improved decision-making and risk management. SADI Int. J. Manag. Account. 2024, 11, 1–10. [Google Scholar]
Sutton, S.G.; Arnold, V.; Holt, M. How much automation is too much? Keeping the human relevant in knowledge work. J. Emerg. Technol. Account. 2018, 15, 15–25. [Google Scholar] [CrossRef]
Kruskopf, S.; Lobbas, C.; Meinander, H.; Söderling, K. The ‘human’ factor in a digital accounting world. In Artificial Intelligence in Accounting, 1st ed.; Kruskopf, S., Lobbas, C., Meinander, H., Söderling, K., Eds.; Routledge: Abingdon, UK, 2022; pp. 37–53. [Google Scholar]
McRae, B.M. Technology and Organizational Decision-Making: A Qualitative Case Study Approach. Ph.D. Thesis, Walden University, Washington, DC, USA, 2019. [Google Scholar]
Podoaba, L.; Armanca, L. The Perception of Professionals in the Financial Accounting Field from Romania Regarding the Digitalization of the Accounting Profession. Ann. “Constantin Brâncuşi” Univ. Târgu Jiu Econ. Ser. 2023, 6, 93–116. [Google Scholar]
Shalhoob, H.; Halawani, B.; Alharbi, M.; Babiker, I. The Impact of Big Data Analytics on The Detection of Errors And Fraud in Accounting Processes. Rev. Gest. Soc. Ambient. 2024, 18, e06115. [Google Scholar] [CrossRef]
Martinez, D.E. Beyond disciplinary enclosures: Management control in the society of control. Crit. Perspect. Account. 2011, 22, 200–211. [Google Scholar] [CrossRef]
Geels, F. Regime resistance against low-carbon transitions: Introducing politics and power into the multi-level perspective. Theory Cult. Soc. 2014, 31, 21–40. [Google Scholar] [CrossRef]
Dai, J.; Vasarhelyin, M.A. Toward Blockchain-Based Accounting and Assurance. J. Inf. Syst. 2017, 31, 5–21. [Google Scholar] [CrossRef]
Kaya, C.T.; Turkyilmaz, M.; Birol, B. Impact of RPA Technologies on Accounting Systems. Muhasebe Finans. Derg. 2019, 82, 235–250. [Google Scholar] [CrossRef]
Mora, L.; Deakin, M. Untangling Smart Cities: From Utopian Dreams to Innovation Systems for Technology-Enabled Urban Sustainability, 1st ed.; Elsevier: Amsterdam, The Netherlands, 2019. [Google Scholar]
Alom, N.B. A comprehensive analysis of customer behavior analytics, privacy concerns, and data protection regulations in the era of big data and machine learning. Int. J. Appl. Mach. Learn. Comput. Intell. 2024, 14, 21–40. [Google Scholar]
Peng, Y.; Ahmad, S.F.; Ahmad, A.Y.B.; Al Shaikh, M.S.; Daoud, M.K.; Alhamdi, F.M.H. Riding the waves of artificial intelligence in advancing accounting and its implications for sustainable development goals. Sustainability 2023, 15, 14165. [Google Scholar] [CrossRef]
Kasiraju, N. Strategic Use of Big Data for Customer Experience and Protection in US Financial Institutions: A Systematic Review. Ph.D. Thesis, University of Maryland University College, Washington, DC, USA, 2024. [Google Scholar]
Gonçalves, M.J.A.; da Silva, A.C.F.; Ferreira, C.G. The Future of Accounting: How Will Digital Transformation Impact the Sector? Informatics 2022, 9, 19. [Google Scholar] [CrossRef]
Căpușneanu, S.; Mateș, D.; Tűrkeș, M.C.; Barbu, C.M.; Staraș, A.I.; Topor, D.I.; Stoenică, L.; Fűlöp, M.T. The impact of force factors on the benefits of digital transformation in Romania. Appl. Sci. 2021, 11, 2365. [Google Scholar] [CrossRef]
Pînzaru, F.; Dima, A.M.; Zbuchea, A.; Vereș, Z. Adopting sustainability and digital transformation in business in Romania: A multifaceted approach in the context of the just transition. Amfiteatru Econ. 2022, 24, 27–44. [Google Scholar] [CrossRef]
Ionașcu, A.E.; Gheorghiu, G.; Spătariu, E.C.; Munteanu, I.; Grigorescu, A.; Dănilă, A. Unraveling digital transformation in banking: Evidence from Romania. Systems 2023, 11, 534. [Google Scholar] [CrossRef]
Rusu, B.; Sandu, C.B.; Avasilcai, S.; David, I. Acceptance of Digital Transformation: Evidence from Romania. Sustainability 2023, 15, 15268. [Google Scholar] [CrossRef]
Grosu, V.; Cosmulese, C.G.; Socoliuc, M.; Ciubotariu, M.S.; Mihaila, S. Testing accountants’ perceptions of the digitization of the profession and profiling the future professional. Technol. Forecast. Soc. Chang. 2023, 193, 122630. [Google Scholar] [CrossRef]
Oncioiu, I.; Bîlcan, F.R.; Stoica, D.A.; Stanciu, A. Digital transformation of managerial accounting-trends in the new economic environment. EIRP Proc. 2019, 14, e06115. [Google Scholar]
Tiron-Tudor, A.; Donțu, A.N.; Bresfelean, V.P. Emerging technologies’ contribution to the digital transformation in accountancy firms. Electronics 2022, 11, 3818. [Google Scholar] [CrossRef]
Coman, D.M.; Ionescu, C.A.; Duică, A.; Coman, M.D.; Uzlau, M.C.; Stanescu, S.G.; State, V. Digitization of accounting: The premise of the paradigm shift of role of the professional accountant. Appl. Sci. 2022, 12, 3359. [Google Scholar] [CrossRef]
Juniardi, E.; Putra, D.M. Digital Transformation in Accounting: Navigating the Future of the Profession Through Systematic Review and Meta-analysis. In Proceedings of the 3rd Jakarta Economic Sustainability International Conference, KnE Social Sciences, Jakarta, Indonesia, 14–15 November 2024. [Google Scholar]
Krosnick, J.A. Questionnaire design. In The Palgrave Handbook of Survey Research, 1st ed.; Vannette, D.L., Krosnick, J.A., Eds.; Palgrave Macmillan: Cham, Switzerland; Stanford, CA, USA, 2018; pp. 439–455. [Google Scholar]
Mohajan, H. Two criteria for good measurements in research: Validity and reliability. Ann. Spiru Haret Univ. 2017, 17, 58–82. [Google Scholar] [CrossRef]
Taherdoost, H. Validity and Reliability of the Research Instrument; How to Test the Validation of a Questionnaire/Survey in a Research. SSRN Electron. J. 2016, 5, 28–36. [Google Scholar] [CrossRef]
Olariu, A. The Impact of Disruptive Technologies on the Accounting Profession. Ph.D. Thesis, West University of Timisoara, Timisoara, Romania, 25 September 2024. [Google Scholar]
Farcane, N.; Bunget, O.C.; Blidisel, R.; Dumitrescu, A.C.; Deliu, D.; Bogdan, O.; Burca, V. Auditors’ perceptions on work adaptability in remote audit: A COVID-19 perspective. Econ. Res.-Ekon. Istraz. 2023, 36, 422–459. [Google Scholar] [CrossRef]
Cokins, G.; Oncioiu, I.; Türkeș, M.C.; Topor, D.I.; Căpuşneanu, S.; Paștiu, C.A.; Deliu, D.; Solovăstru, A.N. Intention to use accounting platforms in Romania: A quantitative study on sustainability and social influence. Sustainability 2020, 12, 6127. [Google Scholar] [CrossRef]
Joshi, A.; Kale, S.; Chandel, S.; Pal, D.K. Likert scale: Explored and explained. Br. J. Appl. Sci. Technol. 2015, 7, 396–403. [Google Scholar] [CrossRef]
Bala, J. Contribution of SPSS in Social Sciences Research. Int. J. Adv. Res. Comput. Sci. 2016, 7, 17–35. [Google Scholar]
Abu-Bader, S.H. Using Statistical Methods in Social Science Research: With a Complete SPSS Guide, 3rd ed, Oxford University Press: Cary, NC, USA, 2021.
Montgomery, D.; Peck, E.; Vining, G. Introduction to Linear Regression Analysis, 5th ed.; John Wiley & Sons: Hoboken, NJ, USA, 2012. [Google Scholar]
Creswell, J.; Clark, V. Designing and Conducting Mixed Methods Research, 1st ed.; Sage Publications: London, UK, 2011. [Google Scholar]
EFAA Digital Competency Maturity Model: At a Glance. 2021. Available online: https://efaa.com/wp-content/uploads/2021/06/20200903_EFAADCMMAtaGlance-FINAL.pdf (accessed on 25 September 2024).
CAFR Launches EFAA’s Digital Competence Maturity Model (DCMM) in Romanian. 2024. Available online: https://www.cafr.ro/cafr-lanseaza-modelul-de-maturitate-a-competentei-digitale-dcmm-al-efaa-in-limba-romana/ (accessed on 25 September 2024).
Liu, H.; Wang, X.; Wang, Z.; Cheng, Y. Does digitalization mitigate regional inequalities? Evidence from China. Geogr. Sustain. 2024, 5, 52–63. [Google Scholar] [CrossRef]
Tsiligiris, V.; Bowyer, D. Exploring the impact of 4IR on skills and personal qualities for future accountants: A proposed conceptual framework for university accounting education. Account. Educ. 2021, 30, 621–649. [Google Scholar] [CrossRef]

Figure 1. Theoretical framework.

Figure 2. Research workflow.

Figure 3. Linear regression graph: experiences regarding the support provided by AI and BDA in performing the profession.

Figure 4. The level of involvement of the Chamber of Financial Auditors of Romania in providing support for understanding and using AI and BDA in auditing.

Figure 5. Respondents’ perception of the current level of professional preparedness of auditors.

Figure 6. The most important tasks in the future considering the impact of AI and BDA.

Figure 7. The most important skills in the context of the accelerated digitalization of the profession through AI and BDA.

Figure 8. The extent to which the modification of International Auditing Standards is considered necessary.

Table 1. Current impact and future trends of AI and BDA in the accounting profession.

Criteria	Impact	AI	BDA
1. Focus	(+)	Enables automated data analysis, pattern recognition, predictive modeling, and natural language processing, enhancing accuracy and efficiency in tasks [34,35,57].	Involves analyzing vast datasets to extract patterns, trends, and correlations, enabling deep insights into financial performance, client behavior, and risk [35,54].
1. Focus	(−)	AI’s complexity may obscure transparency in decision-making processes, as advanced algorithms are often “black boxes” that limit the visibility of decision paths and induce blind spots for the PAs [14,32,61,62].	Can become overwhelming due to the volume and complexity of data, requiring sophisticated tools and interpretation skills to ensure insights are both accurate and actionable [54,63].
2. Primary drivers for adoption	(+)	Efficiency, cost reduction, real-time data needs, and regulatory compliance drive AI adoption, as accounting firms look for ways to optimize operations and reduce manual processing [57,64].	The need for predictive insights, comprehensive analyses, and the ability to make proactive, data-driven decisions fuel the adoption of BDA [65].
2. Primary drivers for adoption	(−)	Requires substantial investments, specialized expertise, and an understanding of both regulatory and security requirements, as AI usage can introduce new compliance risks [66].	Quality and structure of data are crucial, and without a reliable data infrastructure, the insights derived from BDA may be unreliable or irrelevant [67].
3. Technology implementation	(+)	Many accounting firms adopt AI to streamline compliance, reporting processes, and fraud detection, often gaining competitive advantages in accuracy [35,56,64].	Is increasingly adopted to support data-driven financial analysis, enabling firms to better predict financial trends and client needs while identifying risks [56,68].
3. Technology implementation	(−)	Adoption barriers include the high costs of implementation, lack of AI expertise, and potential resistance from staff due to fears of automation replacing jobs [69].	Requires a substantial investment in data infrastructure, including storage, processing capabilities, and analytical tools, which can be costly for accounting firms without robust data resources [70].
4. Skill development	(+)	Promotes the need for PAs to learn AI systems, algorithm interpretation, and continuous learning to stay updated on new AI tools and regulations [71,72].	Necessitates new skill sets, including data management, data cleansing, and advanced analytical skills. Encourages development of data analytics skills, proficiency in statistical modeling, and understanding of data governance [59,73].
4. Skill development	(−)	Advanced technical training is required to understand AI systems, which may limit accessibility for some PAs, particularly those in smaller firms or with fewer resources for training [17,69].	Limited data literacy among PAs could hinder effective adoption, as interpreting and validating BDA results require specialized skills that may not be part of traditional accounting training [17,54].
5. Impact on roles	(+)	Frees PAs from routine tasks like data entry and reconciliations, enabling them to focus on high-value advisory roles such as trend forecasting and advanced risk analysis. This shift moves PAs away from traditional bookkeeping and auditing toward more strategic roles in data analysis and decision support [36,58,71,74,75].	PAs’ roles expand to include data analysis and risk management, enabling them to provide deeper insights into financial trends and guide strategic decision-making with data-driven recommendations [54,58,60,76,77].
5. Impact on roles	(−)	There is a risk that traditional roles may be marginalized as more tasks become automated, potentially reducing the demand for some entry-level positions in accounting [61,78].	Knowledge gaps can emerge if PAs are not adequately trained, which could lead to a mismatch between professional expectations and competencies, limiting their effectiveness in interpreting and using data [60,79].
6. Ethical consideration	(+)	Promotes ethical auditing by producing data-backed decisions that can be more impartial and unbiased, supporting objective outcomes in financial analysis and auditing [80].	Facilitates transparency by providing comprehensive, data-driven insights, enhancing accountability and making it easier to trace decision pathways for auditing purposes [81,82].
6. Ethical consideration	(−)	Algorithmic bias in AI tools can lead to fairness and accountability issues, particularly if biased data or algorithms reinforce existing disparities in decision-making, affecting outcomes for clients and stakeholders [32,69].	Ethical concerns around data ownership, privacy, and confidentiality require careful handling, as mismanagement of data can compromise regulatory compliance and client trust [67].
7. Professional judgment	(+)	Augments professional judgment by providing data-backed insights and predictive analytics, enabling more informed decision-making in complex scenarios [39,83,84,85].	Supports professional judgment with data-supported insights, allowing PAs to analyze trends, identify risks, and make more nuanced recommendations [67].
7. Professional judgment	(−)	Over-reliance on AI outputs can diminish critical thinking, as PAs may defer too heavily to AI-driven insights without thorough validation, risking accuracy and, ultimately, integrity [34,86].	Without sufficient data interpretation skills, professional judgment may be diluted, as PAs may struggle to contextualize or validate BDA insights, potentially leading to misinformed decisions [50,51,87].
8. Human interaction	(+)	Allows PAs to allocate more time to client-facing roles and strategic advisory, enhancing relationships and improving client satisfaction [88].	Fosters collaborative decision-making by providing a data-driven foundation, enabling PAs to engage more effectively with clients through data-supported insights [89,90].
8. Human interaction	(−)	Less direct involvement in basic tasks could reduce engagement and understanding of foundational processes, potentially distancing PAs from core client interactions [32,91,92].	A heavy focus on data may detract from interpersonal interactions and reduce the emphasis on understanding unique client needs, as data analysis may overshadow qualitative assessments [93].
9. Client engagement	(+)	AI insights help enhance client advisory by enabling PAs to present detailed, real-time financial insights and forecasts, strengthening client trust and engagement [88].	Provides PAs with deeper insights into client needs and financial health, enabling more tailored, data-driven client service and improved decision-making support [90].
9. Client engagement	(−)	A reduced need for personalized services may arise as AI tools handle more transactional client needs, potentially making client interactions feel less individualized [30,32,92].	Complexity in data outputs may require careful communication to ensure clients understand analytical findings, as miscommunication could lead to misunderstandings or a perceived lack of transparency [93].
10. Data privacy and security challenges	(+)	Helps meet the increasing demands for regulatory compliance, data accuracy, and fraud detection, addressing significant industry challenges with precision [94].	Manages complex data requirements, supporting compliance and helping firms better understand patterns that could indicate risks, such as fraud or financial instability [95].
10. Data privacy and security challenges	(−)	Cybersecurity risks and ethical concerns around AI fairness and transparency pose challenges, as algorithmic biases or misuse of data could undermine trust in AI-based financial services [7,32,96,97,98,99,100].	Privacy breaches and data security are critical risks, as vast amounts of sensitive financial data require stringent confidentiality and protection protocols, which can be difficult to manage and enforce consistently [101].
11. Opportunities and implications for sustainable development	(+)	AI improves efficiency in audits, tax preparation, and compliance checks, allowing firms to expand their service offerings and deliver more value. AI-driven automation in accounting can contribute to Sustainable Development Goals (SDGs) by improving efficiency and reducing resource consumption, aligning with SDG 8 (Decent Work and Economic Growth) [71,74,75,102].	Enables PAs to provide data-driven insights and strategic recommendations, supporting clients with actionable intelligence and identifying opportunities for process improvements. Additionally, BDA may enable businesses to make sustainable decisions that support SDG 9 (Industry, Innovation, and Infrastructure) and SDG 16 (Peace, Justice, and Strong Institutions) [35,54,102].
	(−)	Insufficient understanding of AI processes may hinder optimal use and adoption, as PAs may underutilize tools due to unfamiliarity with AI functions or capabilities [29].	Overwhelming data volumes can lead to data overload, making it challenging for PAs to focus on the most relevant insights or manage data effectively without advanced filtering and data management strategies [54,63].
12. Legitimacy and outcome for the profession	(+)	Positions PAs as strategic advisors with advanced technical competencies, enabling them to play a vital role in guiding firms through complex data environments and regulatory landscapes [36,64].	Empowers PAs to make data-informed decisions, providing stronger credibility and trust with clients by offering evidence-based recommendations and proactive financial insights [103].
12. Legitimacy and outcome for the profession	(−)	Over-reliance on technology risks eroding traditional accounting skills, as automation increasingly handles foundational tasks, reducing PAs’ involvement in core practices. This shift may raise concerns about the profession’s legitimacy, making it essential for PAs to maintain trust and clearly demonstrate the value they bring beyond automated processes [34,50,51,57,61].	Finding a balance between traditional skills and data expertise is essential to avoid a narrow focus on data at the expense of core financial analysis skills, as some clients may still value human intuition and experience alongside data-driven insights [50,51,59,94].

Note: Text in italics indicates challenges or limitations associated with each criterion related to AI and BDA adoption in the accounting profession.

Table 2. Population of the statistical sample.

Active Members—2022	Registered	Reporting Audit Activities	Reporting Financial Statement Audits and Statutory Audits	Reporting Statutory Audits	Reporting Financial Audits	Reporting Both Statutory and Financial Audits
Individual Auditors	4240	538	369	275	49	45
Corporate Auditors	1023	780	643	408	58	177
Total	5263	1318	1012	683	107	222

Table 3. Statistical sample size.

Probability	94%
Statistical error	6%
Total population	222 = (45 + 177)
Sample size	117

Table 4. Cross-tabulation calculation: respondents’ gender/age.

Cross-Tabulation
Count
		Age					Total
		Under 25 Years Old	Between 25 and 30 Years Old	Between 30 and 45 Years Old	Between 46 and 60 Years Old	Over 60 Years Old	Total
Gender	Female	0	1	6	22	1	30
Gender	Male	0	4	22	58	4	88
Total		0	5	28	80	5	118

Table 5. Cross-tabulation calculation: respondents’ gender/experience in the audit field.

Cross-Tabulation
Count
		Experience in Financial Accounting					Total
		Up to 2 Years	Between 2 and 5 Years	Between 5 and 10 Years	Between 10 and 20 Years	Over 20 Years	Total
Gender	Female	0	0	3	2	25	30
Gender	Male	0	2	8	11	67	88
Total		0	2	11	13	92	118

Table 6. Cross-tabulation: BDA tools and AI technology usage in work activity/first experiences while using AI and BDA and the perception of the importance of digitalization in the profession.

Cross-Tabulation
Count
		Initial Experiences in Using AI and BDA in Daily Activities			Importance Assigned to the Digitalization of the Profession
		Very Easy and Intuitive	Initially Complicated, but It Became Quite Simple with Use	Very Complicated, Requiring the Assistance of a Specialist	Important	Very Important
Utilizing particular BDA tools and AI technology for work-related tasks	Yes	3	52	18	21	52
	No	1	34	10	22	23
Total		4	86	28	43	75

Table 7. Cross-tabulation calculation: initial experiences in using AI and BDA in professional daily activities/respondents’ age.

		Cross-Tabulation
		Count
		Age					Total
		Under 25 Years Old	Between 25 and 30 Years Old	Between 30 and 45 Years Old	Between 46 and 60 Years Old	Over 60 Years Old	Total
Initial experience in using AI and BDA in daily activities	Very easy and intuitive	0	2	2	0	0	4
	Initially challenging but became simple with continued use	0	3	18	62	3	86
	Very complex, requiring specialist assistance	0	0	8	18	2	28
Total		0	5	28	80	5	118

Table 8. Cross-tabulation of frequencies: the importance of the digitalization of the profession/level of interest regarding the digitalization of the profession.

Cross-Tabulation
Count
		Interest in the Digitalization of the Profession					Total
		Very Low	Low	Neutral	Medium	To a Large Extent	Total
Perceived importance of digitalization	Important	0	0	6	7	30	43
Perceived importance of digitalization	Very Important	0	1	4	2	68	75
Total		0	1	10	9	98	118

Table 9. Cross-tabulation: level of interest regarding the digitalization of the profession/the support provided by technologies in the work performed.

Cross-Tabulation
Count
		Support Provided by AI and BDA in the Work Performed		Total
		Does Not Provide Support in Terms of the Efficiency and Effectiveness of Performing Professional Activities	Provides Support in Terms of the Efficiency and Effectiveness of Performing Professional Activities	Total
Interest in the digitalization of the profession	Very low	0	0	0
	Low	0	1	1
	Neutral	1	9	10
	Medium	2	7	9
	To a largeextent	0	98	98
Total		3	115	118

Table 10. Cross-tabulation: level of interest regarding the digitalization of the profession/the level of preparedness for using AI and BDA.

Cross-Tabulation
Count
		Preparedness for Using AI and BDA		Total
		No	Yes	Total
Interest in the digitalization of the profession	Very low	0	0	0
	Low	0	1	1
	Neutral	2	8	10
	Medium	2	7	9
	To a large extent	1	97	98
Total		5	113	118

Table 11. Cross-tabulation: level of interest regarding the digitalization of the profession/perception of the future of the accounting profession.

Cross-Tabulation
Count
		Perception of the Future of the Accounting Profession		Total
		The Profession Will Undergo Significant Redefinition Due to the Implementation of AI and BDA	Favorable, as AI and BDA Are Seen as Supporting Professional Progress	Total
Interest in the digitalization of the profession	Very low	0	0	0
	Low	0	1	1
	Neutral	0	10	10
	Medium	5	4	9
	To a large extent	0	98	98
Total		5	113	118

Table 12. Cross-tabulation: perception of the future of the accounting profession/respondents’ age.

Cross-Tabulation
Count
		Age					Total
		Under 25 Years Old	Between 25 and 30 Years Old	Between 30 and 45 Years	Between 46 and 60 Years	Over 60 Years	Total
Perception of the future of the accounting profession	The profession will undergo significant redefinition due to the implementation of AI and BDA	0	0	0	5	0	5
Perception of the future of the accounting profession	Favorable, as AI and BDA are seen as supporting professional progress	0	5	28	75	5	113
Total		0	5	28	80	5	118

Table 13. Linear regression: experiences regarding the support provided by AI and BDA in performing the profession—model summary.

Model Summary ^b
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	0.597 ^a	0.356	0.339	0.129
Interest in the digitalization of the profession How AI and BDA have led to the transformation of the profession Role of AI and BDA in the accounting profession
Perception of the support provided by AI and BDA in the performance of the profession

^a. Predictors: (Constant). ^b. Dependent Variable.

Table 14. Linear regression: experiences regarding the support provided by AI and BDA in performing the profession—ANOVA.

ANOVA ^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1.041	3	0.347	20.998	<0.001
	Residual	1.883	114	0.017
	Total	2.924	117
Experiences regarding the support provided by AI and BDA in the performance of the profession
Interest in the digitalization of the profession How AI and BDA have led to the transformation of the profession Role of AI and BDA in the accounting profession

^a. Dependent Variable. ^b. Predictors: (Constant).

Table 15. Linear regression: experiences regarding the support provided by AI and BDA in performing the profession—coefficients.

Coefficients ^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
Model		B	Std. Error	Beta	t	Sig.
1	(Constant)	0.138	0.122		1.134	0.259
	Interest in the digitalization of the profession	0.047	0.018	0.192	2.533	0.013
	How AI and BDA have led to the transformation of the profession	0.041	0.018	0.172	2.271	0.025
	Role of AI and BDA in the accounting profession	0.097	0.015	0.488	6.378	<0.001

^a. Dependent Variable: Experiences regarding the support provided by AI and BDA in the performance of the profession.

Table 16. Cross-tabulation: experience regarding the support provided by AI and BDA in performing the profession/the level of interest in the digitalization of the profession/experience of how AI and BDA have led to the transformation of the profession/experience regarding the role of AI and BDA in the accounting profession.

Cross-Tabulation
Count
		Experiences Regarding the Support Provided by AI and BDA in Performing the Profession		Total
		Do Not Provide Support in Terms of the Efficiency and Effectiveness of Performing Professional Activities	Provide Support in Terms of the Efficiency and Effectiveness of Performing Professional Activities	Total
Interest in the digitalization of the profession	Very low	0	0	0
	Low	0	1	1
	Neutral	1	9	10
	Medium	2	7	9
	To a large extent	0	98	98
How AI and BDA have led to the transformation of the profession	Not at all	1	2	3
	To a small extent	1	2	3
	To a moderate extent	0	0	0
	To a large extent	0	97	97
	Completely	1	14	15
Role of AI and BDA in the accounting profession	Not at all important	0	0	0
	Slightly important	3	4	7
	Neutral	0	2	2
	Important	0	19	19

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MDPI and ACS Style

Deliu, D.; Olariu, A. The Role of Artificial Intelligence and Big Data Analytics in Shaping the Future of Professions in Industry 6.0: Perspectives from an Emerging Market. Electronics 2024, 13, 4983. https://doi.org/10.3390/electronics13244983

AMA Style

Deliu D, Olariu A. The Role of Artificial Intelligence and Big Data Analytics in Shaping the Future of Professions in Industry 6.0: Perspectives from an Emerging Market. Electronics. 2024; 13(24):4983. https://doi.org/10.3390/electronics13244983

Chicago/Turabian Style

Deliu, Delia, and Andrei Olariu. 2024. "The Role of Artificial Intelligence and Big Data Analytics in Shaping the Future of Professions in Industry 6.0: Perspectives from an Emerging Market" Electronics 13, no. 24: 4983. https://doi.org/10.3390/electronics13244983

APA Style

Deliu, D., & Olariu, A. (2024). The Role of Artificial Intelligence and Big Data Analytics in Shaping the Future of Professions in Industry 6.0: Perspectives from an Emerging Market. Electronics, 13(24), 4983. https://doi.org/10.3390/electronics13244983

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