Audit Empowering AI Leadership


Introduction | Responsibilities | Oversight | Discussion guide | Agenda | Resources | Endnotes

View this module as a PDF here

View this module in Spanish

Other modules:

Home | Audit | Brand Strategy | Competitive Strategy | Customer Strategy | CybersecurityEthics | Governance | Operations Strategy | People and Culture | Responsibility | Risk | Sustainable DevelopmentTechnology Strategy | Glossary


Why is this a board issue?

The use of artificial intelligence (AI) is already rapidly reaching all corners of business in ways that affect Audit Committee responsibilities, both directly and indirectly. And as time passes, AI use cases will become ubiquitous. Already, a company may use AI directly in its financial systems, financial planning and analysis (FP&A), internal audit processes, fraud detection, asset management or other related functions. In addition, a company’s use of AI in its products, services and business operations could affect its financial results and investment decisions, and may require specific controls, audits or other governance and oversight. More and more, external auditors are incorporating AI into the actual audit process, both to enable greater transaction testing and to automate what are today manual tasks. Evolving laws and regulations are certain to have a growing impact upon a company’s AI, data and privacy programmes. This module focuses on the Audit Committee’s responsibilities specifically as they intersect with AI, as described further below. (Risk oversight is covered in a separate module).


Companies are integrating use of AI across the business.

As companies’ use of AI in product and service offerings, production, sales and distribution, maintenance and quality control expands, AI will have an ever greater impact upon a company’s financial results and reporting. For example, the use of machine learning and data analytics in FP&A activities promises to have a significant impact on management’s investment decisions across product lines, research and development, go-to-market approaches and staffing levels. To make sound decisions, management must understand where and how AI is being used, the underlying assumptions and data used to train the models, why a particular model has been chosen, how often the models must be retested and retrained, and the realistic predictive value (or limit) of the tools. Few FP&A personnel today possess the technical skills that will be critical to success in a predictive analytics/AI-driven world.

The company’s financial statements reflect its performance in a given time period and typically include comparisons with a prior period. In the US, for example, management must discuss and analyse present and past financial results in securities filings. As AI increasingly affects financial performance, management will face greater complexity in assuring financial statement integrity and providing transparent disclosure to investors, employees and other stakeholders. Transparency will influence the model selection, as it will not be acceptable for management to be unable to explain how, why or what underpins material decisions or how a particular AI-driven outcome is consistent with the company’s business strategy. Therefore, understanding the ways in which AI is deployed within an organization is increasingly critical to understanding financial statements. To discharge its oversight responsibilities, the Audit Committee must satisfy itself that management has taken the appropriate steps to ensure that the use of AI has not compromised financial statement integrity.


Internal audit functions are increasingly implementing AI to support legal compliance, detect fraud and mitigate risk.

A recent survey of internal audit stakeholders indicated that 13% of respondents have already implemented AI solutions as part of their internal audit process, while another 16% have plans to do so.[1] Within the internal audit function, companies are using AI to collect, analyse and act upon massive amounts of data to help ensure legal compliance, detect fraud and mitigate risk. However, the efficacy of AI in each of these use cases relies on the availability and quality of the required data and the ability of the internal audit staff to review, analyse and make sense of the results. Internal audit heads will need to work to gather the necessary data in a form that is compatible with the AI tools being used to ensure the intended outcomes are reliably achieved. Initially, the use of AI in internal audit operations will entail little more than the application of statistical models and human-supplied thresholds. As internal auditors become more comfortable with applied data science, they will use ever more complex algorithms and data sources. To succeed, internal audit and legal staff will require appropriate training and skills to understand the tools, the inputs, the limitations and the meaning of the outputs with respect to legal compliance and fraud detection/prevention.


External auditors are expected to rapidly integrate AI into all parts of the audit process.

In recent years, each of the Big Four accounting firms has announced initiatives to integrate AI tools into the audit process. For instance, auditors are now using natural language AI tools to extract important terms from lease agreements and other contracts to significantly decrease the amount of time that audit staff spends reviewing such contracts. These terms are critical to determining when income and expense may be recognized for income-statement and balance-sheet purposes. Audit Committee members are ultimately responsible for overseeing the qualifications of the independent auditors, the auditor’s audit plan and the performance of the audit. Therefore, the Audit Committee needs to understand the extent to which management and the independent auditors use AI tools in the preparation of financial statements, in the audit process and in the submission of periodic financial reports and filings required under applicable securities laws.


According to the G20/OECD Principles of Corporate Governance:[2]

Board members should act on a fully informed basis, in good faith, with due diligence and care, and in the best interest of the company and the shareholders. (Principle VI.A)

These principles apply equally to the members of the Audit Committee, who are primarily responsible for:

  • Overseeing the integrity of all financial statements, the content of financial reporting, and the implementation of and compliance with suitable internal controls
  • Overseeing the qualifications, independence and performance of the company’s external auditors
  • Overseeing the internal audit function, where applicable
  • Overseeing risk management programmes and policies (in those instances where the board has not constituted a separate Risk Committee)
  • Overseeing compliance with laws and regulations.
The board should fulfill certain vital functions, including ensuring the integrity of the corporation’s accounting and financial reporting systems, including the independent audit, and that appropriate systems of control are in place, in particular, systems for risk management, financial and operational control, and compliance with the law and relevant standards. (Principle VI.D.7)

Given the increasing role of AI in a company’s business, operations, internal audit function and external auditors’ process, in order to assist the board in fulfilling its responsibilities to shareholders and other stakeholders, Audit Committee members should make a diligent and good-faith effort to:

  • Understand management’s approach to assessing, implementing and managing AI and AI-related risks across the company
  • Review the company’s internal controls and governance of AI systems
  • Discuss with management its present and planned use of AI within the enterprise
  • Discuss the role of AI in both the internal and external audit processes with the relevant company and independent auditor personnel
  • Learn about the risks, benefits and unknowns associated with using AI as part of the audit processes
  • Discuss management’s compliance with applicable legal and regulatory requirements relating to AI
  • Include within its annual review of the qualifications, independence and performance of the external audit team, the auditor’s use of AI in connection with any company audit engagement as well as the capabilities of the audit team in using the types of AI tools being deployed in the engagement
  • Require that internal audit personnel have access to appropriate training and support.

In addition, Audit Committee members at companies that have yet to incorporate AI as part of the internal audit and risk management functions should evaluate whether implementing AI solutions is necessary and/or appropriate to fulfil their responsibilities. Factors to consider include:

The costs of implementing AI solutions, weighed against anticipated risks and perceived benefits;

  • This includes understanding at a minimum: a) the ability and limits of the AI tools themselves; b) the extent and quality of the data available to deploy with the AI tools; c) the training and oversight of the personnel responsible for deploying the AI tools; d) the training and oversight of the AI tools themselves; and e) how the results from AI tools will be assessed for their accuracy, transparency, efficacy and impact on the business.

The efficacy of existing anti-fraud and risk-management solutions, controls and processes;

The capacity of such technologies to explain, describe and attribute their results and analytical process, and;

The regulatory regimes applicable to the company and the jurisdictions in which the company operates.

  • For instance, the U.S. Foreign Corrupt Practices Act makes it illegal for any company that has securities registered in the United States or that has its principal place of business within the United States to make improper payments to government officials anywhere in the world. Given this broad scope, companies with significant US and global operations may be best served by incorporating AI-driven data analytics tools to aid in the identification of potentially improper transactions.

The analysis in this section is based on general principles of corporate governance, including the G20/OECD Principles of Corporate Governance, 2015. It does not constitute legal advice and is not intended to address the specific legal requirements of any jurisdiction or regulatory regime. Boards are encouraged to consult with their legal advisers in determining how best to apply the principles discussed in this module to their company.


Recommendations for responsible Audit Committee oversight of AI:

Become and remain educated on AI developments that may affect the company’s business, its financial reporting, data usage, transfer, and storage, risks, benefits and ethical considerations (such as using this toolkit).

Require that the Audit Committee receives periodic reports from management regarding the company’s use of AI.

  • Discussions with management should focus on: 1) a framework for governance of and decision-making relating to AI; 2) oversight, quality and accountability of AI tools; 3) risks to the company in connection with the use of AI; and 4) the impact of AI on financial performance.

Be aware of the costs and benefits of implementing AI solutions, especially as compared to other options available.

Encourage internal audit personnel to evaluate potential AI tools and provide sufficient resources to ensure successful implementation.

Regularly discuss the implementation and accountability of AI as part of the audit process with external auditors.

  • Discussions should focus on maintaining human oversight of the audit process, identifying areas in which AI is/is not appropriate, measures and controls to ensure that AI achieves its intended purpose and does not cause unintended harm.

Discuss and understand how the use of AI intersects with the company’s data policies, legal requirements and other business conduct rules.

Continue to revise AI governance standards and procedures in light of evolving business conditions and AI technologies.

  • This will require Audit Committee members to remain informed about developing AI technologies both in the company’s industry and in the audit field.

Monitor legal and regulatory developments relating to AI, data and privacy.

Recognize that the Audit Committee is ultimately responsible for assisting the board in overseeing management in its preparation of accurate and complete financial statements, as well as the qualifications, independence and performance of the company’s external auditors.

Discussion guide

The Audit Committee should set aside time at regular intervals to consider the following questions regarding financial statement and audit integrity and AI:

  1. Which internal applications and processes within the company use AI technology today? What uses are on the horizon and/or within management’s three- and five-year plans?
  2. Within the company, and for each such AI tool, who supervises its use and evaluation? How familiar is management with those uses and how they are supervised and according to what internal standards and controls?
  3. What controls are in place to evaluate and require that the use of AI will achieve its intended purpose on an ongoing basis?
  4. What controls are in place to evaluate and require that the use of AI will not cause unintended harms?
  5. In what ways (if any) does AI affect the preparation of the company’s financial statements, directly or indirectly?
  6. Could the company’s internal audit function benefit from implementing AI solutions (e.g. advanced data analytics to review a large number of contracts and detect possible fraud)? If so, who within the company will oversee the deployment of such tools, what is their reporting responsibility and what budget should be approved for such solutions and the related training of the internal audit personnel?
  7. What are the potential risks (if any) of using AI solutions as part of the company’s internal controls and internal audit function? What can be done to mitigate these risks?
  8. Does the company’s management allow AI tools to be deployed in such a way that they replace management’s independent judgment and oversight?
  9. What role does AI play in the external audit? What controls over AI does the company’s external auditor have in place?
  10. Has the company’s management appropriately discussed the impact of AI solutions on the company’s financial statements with the external auditors?
  11. Does the external auditor staff (including the engagement partner and senior members of the engagement team) have the background and training to understand the appropriate use and limitations of AI by the company and in the audit itself?
  12. As the prevalence and number of AI solutions continue to grow, what steps will the company need to take to ensure that these solutions are implemented in such a way as to allow the Audit Committee to effectively maintain oversight of both the internal controls over financial reporting and the audit process?
  13. Are the company’s cybersecurity programs adequate to prevent tampering with data sources used to train algorithms as well as the AI models employed by the company that may affect the financial statements?
  14. Are the company’s data policies in line with the use of AI solutions that may affect the financial statements? Are they compliant with relevant laws?
  15. Are there additional caveats, risk factors or other disclaimers that need to be incorporated to accommodate the use (or non-use) of AI tools for particular audit functions?
  16. Does the use of AI tools in any way affect the schedule, timing or content of the company’s Audit Committee processes and procedures?
  17. What resources would the Audit Committee like to have to understand and/or keep up to date with the use of AI within the company?
  18. Does the Audit Committee contain one or more members with knowledge and/or experience in relevant AI practices? Has the committee designated a member with responsibility for acquiring such knowledge?


  1. Request from management a periodic report on current or anticipated use(s) of AI within the company that: a) assist internal audit functions; b) assist external audit functions; and c) indirectly affect the company’s financial reporting and results. Consider commissioning an annual tutorial on available tools. (See Discussion guide, above)
  2. Consider company-specific guidelines for any AI tools that do or could affect financial statements and/or financial reporting, including standards for vendors and outside auditors who use such tools. Such guidelines might include data policies, accuracy targets, ethical standards and safeguards, reporting and transparency requirements, the capacity to interrogate results, updating requirements and so forth.
  3. Set up a regular agenda item for [every] Audit Committee to review the current and upcoming uses of AI within the company, including a review of any problems or challenges that have arisen with respect to such usage.
  4. Request regular reports from management on the deployment and development of AI tools within the company insofar as they affect the audit function.
  5. Request regular reports from the legal function to obtain an understanding of prevailing legal requirements and standards with respect to the use of AI, which may differ from jurisdiction to jurisdiction, and which may change over time.
  6. Require that the company’s code of conduct or equivalent policies include clear statements regarding the company’s commitment to the ethical use of AI in the company’s business.


(All links as of 20/7/19)


(All links as of 20/7/19)

Other modules:

Home | Audit | Brand Strategy | Competitive Strategy | Customer Strategy | Cybersecurity | Ethics | Governance | Operations Strategy | People and Culture | Responsibility | Risk | Sustainable Development | Technology Strategy | Glossary