Implementing AI at The Organization Level: A Review of How CPA Firms Are Adopting AI

Implementing AI at the Organization
Level: a review of how CPA firms are

adopting AI
Presented by: Ivy Munoko
Why do we need AI in auditing?
• Humans experience • Machines have fast

Information processing and information processing
memory capacity capabilities, increasing
limitations (Hogarth 1980) memory capacity and pattern
recognition capabilities
• Auditors are required to
understand both private • Humans are still needed in
and public client the Man + Machine model,
information – overload!! - since AI intelligence is still
information will increases 10x narrow
every five years (Khan, et al.
2014)
In this data explosive age, auditors need a decision aid to sift

through data and provide insights 2
Current implementations: All Big 4 accounting
firms are reporting the use of these AI blocks
Big AI / Natural Speech
Machine Machine Intelligent
Smart Language
Learning Vision RPA Recognition
Analytics Processing
• Fraud • discover • Synthesis of • OCR + • Test of • Decode

detection facts and text e.g. Machine transactions conversation
relations review of learning to
• Review full that are contracts, extract data • Document • Chat bots
population difficult for vendor from images workpapers
for outliers the human invoices,
• Digital
e.g. KPMG mind e.g. emails, • Drones + • GL review Assistants
Clara, EY PwC Halo transcribed IoT to
performs conversation e.g. EY
Helix GL perform Goldie
risk e.g. Deloitte • Bank
inventory
assessment Argus inspection confirmation
3
Current implementations: Small / medium size
accounting firms are using AI SaaS
Ensemble AI: Combines
Machine learning with Domain
expertise / business rules and
statistical methods to:
-gain actionable insight into
large data
-review 100% of data
-sample from outliers
-perform risk assessments
4
5 in
Source: Munoko, Ivy, Helen L. Brown-Liburd, and Miklos Vasarhelyi. "The Ethical Implications of Using Artificial Intelligence
Auditing." Journal of Business Ethics: 1-26.
Stopping point:
1. Please visit any of the Big 4 websites (Deloitte, EY, KPMG or

PwC)
2. Search for news article or publication about an Artificial
Intelligence project or software that they are using for
auditing.
3. Please provide the name and description of what the AI
software does. Also, please provide a link to the page where
you obtained this information.
4. Please think about the capabilities and challenges of the AI
software for the Big 4 firm, and provide a brief summary of
these. The previous slide can be a guide.
6
Future of audit: Case of how Deloitte plan to roll
out AI enabled audit
Simplify
Digitize Advanced
and Automate Intelligence
tasks analytics
standardize
7
Workings of AI
8 in
Source: Munoko, Ivy, Helen L. Brown-Liburd, and Miklos Vasarhelyi. "The Ethical Implications of Using Artificial Intelligence
Auditing." Journal of Business Ethics: 1-26.
Current applications of AI in accounting and auditing
As AI shifts Group 1: Assisted AI: Support lower level decisions

from assisted
towards
Examples: Chatbots assisting auditors retrieve information
autonomous,
the tool
sophistication, Group 2: Augmented AI: Support high risk decisions
resultant
benefits as Examples: Selecting transactions for testing
well as the
Group 3: Autonomous AI: Assumes decision making
risks increase
Examples: Testing transactions
9
Current applications of AI in accounting and auditing, and the ethical
implications
• Assisted AI
– performs tasks specific to a process, but ultimately the human is the one
responsible for making the decisions
– By 2025 30% of audits would be performed by AI (World Economic Forum
2015)
– Potential ethical implications:
• the lack of transparency (i.e., opacity) into the workings of AI, and a lack of
explanations behind AI’s actions may result in a responsibility gap
• enforcement of data privacy, data protection, and data quality, especially when
AI is used across the data of different clients
• profiling’ that consists of any form of automated processing of personal data
evaluating the personal aspects of an individual
• uncorrected biases in the underlying data used by companies for predictive
tasks
10
Step 2: Current applications (based on artifacts) of AI in accounting and
auditing, and the ethical implications
• Augmented AI
– AI does the heavy lifting of computing and analysis, delivering more
profound insights towards more informed decisions and actions
– By combining AI with the human, the process is enhanced (augmented) in
comparison to the purely manual process
– While AI can analyze ‘billions of data points in milliseconds, it is important
that firms are transparent on the human limitations that come with
Augmented AI, to set the right expectations for their clients and users of
their financial reports,
– Augmented AI’s power over the user potentially leads to overreliance
which may impact judgement and decision making
– Given that firms are proposing to use AI for more complex issues, if the
algorithms that make decisions about complex tasks are never
contradicted, then auditors may essentially abdicate their judgement
responsibilities by unquestioningly accepting the recommendations of AI
11
Step 2: Current applications of AI in accounting and auditing, and the
ethical implications
• Autonomous AI
– the most enhanced AI, which can operate on its own without
human intervention
• who is accountable for AI’s action
– who is accountable for AI’s action when things go wrong
(responsibility gap)
• Greater autonomy and opacity
– still much to learn about whether AI demonstrates a level of
intuitive intelligence consistent with a human expert
• Intuition deals more with “gut feelings” vs. intelligence which is
related to logic or a calculated decision making process
• Auditors are required to exhibit professional skepticism during
all phases of the audit
12
Stopping point:
5. Do you think the application you found from the Big 4 firm’s
website is Assisted AI, Augmented AI or Autonomous AI?
6. Have any other possible challenges of the AI software come to

mind, in addition to the challenges you have already described
in question 4? Please add any new insights in a separate
paragraph.
13
What is the role of the future accountant?
Huang, Ming-Hui, and Roland T Rust (2018)
Shift from
preparing
workpapers
towards
more critical
thinking
14
Strategic Finance
Paper on ethics and AI
Real world Data is used to Throughout its
Algorithms
Data
Use
data is identify use, AI
continuously patterns and updates its
fed into AI develop models based
models for on new data it
predictive is exposed to
tasks
Examples of ‘What could go wrong’ with AI systems
1. Data collection and usage by AI 4. Complex AI models resulting in
leads to privacy / security violations? unexplainable and therefore
undefendable decisions?
2. Data inaccuracy? Therefore
algorithm inaccuracy? 5. Users of AI relying wholly on the
system and not performing
3. Biased data / data that does not reasonableness tests of AI output?
represent the true population result in
unfair / incorrect decisions made by 6. Regulations violated by AI use?
algorithms? (e.g. HIPAA, European Union
Regulation 2016/679) 15
Stopping point:
7. Do you have any recommendations on how the Big 4 firm can

overcome the challenges that you highlighted for question 4
and 6 ?
16
Thank you!
17

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Implementing AI at the Organization

Level: a review of how CPA firms are

• Humans experience • Machines have fast

In this data explosive age, auditors need a decision aid to sift

• Fraud • discover • Synthesis of • OCR + • Test of • Decode

-review 100% of data

-sample from outliers

-perform risk assessments

1. Please visit any of the Big 4 websites (Deloitte, EY, KPMG or

As AI shifts Group 1: Assisted AI: Support lower level decisions

6. Have any other possible challenges of the AI software come to

Huang, Ming-Hui, and Roland T Rust (2018)

7. Do you have any recommendations on how the Big 4 firm can

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