AI in Accounting: 7 Risks Companies Should Review Before Their Next Audit

Artificial intelligence is quickly becoming part of everyday business operations. Companies are using AI to summarize documents, draft policies, analyze data, assist with reconciliations, support reporting, and improve efficiency.

Used responsibly, AI can be a valuable tool.

But when AI touches accounting, financial reporting, internal controls, or audit support, it also creates new risks that management should understand. The issue is not whether AI is “good” or “bad.” The issue is whether the organization has the right governance, review, documentation, and controls around how AI is being used.

If your company is using AI in accounting or finance, here are seven risk areas to review before your next audit.

Sensitive Data Exposure

One of the biggest risks is entering confidential information into AI tools without understanding where that data goes, how it is stored, or who can access it.

Accounting and finance teams often work with sensitive information, including:

• Financial statements

• General ledger activity

• Payroll data

• Employee information

• Customer or patient information

• Vendor records

• Bank information

• Tax records

• Contract terms

• Audit documentation

If employees copy and paste sensitive data into an AI platform without approval, the company may create privacy, cybersecurity, confidentiality, or regulatory risk.

This is especially important for organizations in healthcare, financial services, government contracting, nonprofit grant compliance, and other regulated industries.

Management should ask:

• Are employees allowed to use AI tools with company data?

• What types of data are prohibited from being entered?

• Has the AI tool been reviewed by IT, legal, compliance, or management?

• Does the vendor retain or use company data to train its models?

• Are employees trained on what information should never be entered into public AI tools?

AI use should be addressed in company policy before sensitive data is exposed.

Unreviewed AI Outputs

AI can produce answers that sound confident but may be incomplete, outdated, inaccurate, or unsupported.

In accounting, that matters.

If AI is used to draft journal entry explanations, summarize contracts, prepare reconciliations, analyze variances, or assist with audit schedules, the output still needs professional review. AI should not replace management judgment, technical accounting knowledge, or supervisory review.

Examples of risky AI use may include:

• Accepting AI-generated account coding without review

• Using AI to summarize lease or debt agreements without checking the source documents

• Relying on AI-generated revenue recognition conclusions

• Allowing AI to draft financial statement disclosures without technical review

• Using AI-generated audit support without verifying accuracy

A useful rule is simple: AI can assist, but a qualified person should still review, approve, and take responsibility for the final work product.

No Audit Trail or Documentation

Auditors need evidence. Management needs documentation. AI can create problems if the process cannot be explained or reproduced.

For example, if AI helped prepare an analysis, management may need to document:

• What tool was used

• What data was provided

• What prompt or instructions were used

• What output was generated

• Who reviewed the output

• What changes were made

• What source documents support the final conclusion

Without documentation, it may be difficult to support the work during an audit. This is especially important for significant estimates, technical accounting conclusions, management review controls, compliance testing, and financial reporting support.

If AI is used in a process that affects accounting records, audit evidence, or management review, the company should consider how that use will be documented.

Inaccurate or Incomplete Results

AI outputs depend on the quality of the information provided and the way the request is structured. If the data is incomplete, the prompt is unclear, or the tool lacks context, the result may be wrong.

In accounting and audit readiness, small errors can create larger problems.

For example, AI may:

• Misinterpret contract terms

• Summarize a policy incorrectly

• Miss exceptions in a reconciliation

• Apply the wrong accounting concept

• Overlook industry-specific requirements

• Produce outdated regulatory information

• Create a misleading analysis from incomplete data

This risk is especially important when AI is used in areas involving judgment, estimates, compliance, or technical standards.

Management should not assume that a polished AI answer is a correct answer. The output should be compared to source documents, current guidance, and the company’s actual facts.

Third-Party AI Vendor Risks

AI is not always used directly through a chatbot or standalone platform. Many software vendors are adding AI features into accounting systems, payroll platforms, billing tools, expense systems, analytics dashboards, and cloud applications.

That means AI risk may already exist inside tools your company uses.

Vendor-related questions may include:

• What AI features are included in the software?

• Can those features be turned on or off?

• What company data does the tool access?

• Is data used to train vendor models?

• What security controls does the vendor have?

• Is there a SOC report or other security documentation?

• Does the vendor use subcontractors or other AI providers?

• What happens if the system produces an incorrect output?

For audit readiness, vendor AI tools can also affect system access, change management, data integrity, cybersecurity, and internal control documentation.

Companies should understand not only which AI tools employees are using, but also which AI features are embedded in existing software.

Lack of Policies and Approvals

Many organizations are already using AI informally, even if they do not have an official AI policy.

That creates risk.

Without clear rules, employees may make inconsistent decisions about what tools to use, what information to enter, and how much they can rely on AI-generated results.

An AI policy does not need to be overly complicated. At a minimum, it should address:

• Approved and prohibited AI tools

• Types of data that may not be entered

• Required review of AI outputs

• Documentation expectations

• Approval requirements for new AI tools

• Vendor review procedures

• Cybersecurity and confidentiality expectations

• Employee training

• Consequences for improper use

From an internal control perspective, the goal is to create consistency, accountability, and oversight.

Overreliance on AI

AI should support decision-making, not replace professional judgment.

This is especially important in accounting, internal audit, audit readiness, and compliance work. Many areas require judgment, context, skepticism, and knowledge of the organization’s operations.

Overreliance on AI may lead to:

• Missed errors

• Weak review procedures

• Unsupported conclusions

• Reduced professional skepticism

• Inconsistent application of policies

• Inaccurate financial reporting support

• Control deficiencies

AI can help teams work faster, but speed should not come at the expense of accuracy, documentation, or accountability.

A good question to ask is:

“If this output is wrong, who would catch it?”

If the answer is unclear, the process may need stronger controls.

What Companies Should Do Now

AI risk management does not have to be overwhelming. Companies can start with a few practical steps.

Identify Where AI Is Being Used

Start by asking accounting, finance, operations, IT, HR, and compliance teams where AI tools are being used. Include both standalone tools and AI features built into existing software.

Classify the Risk

Not all AI use carries the same level of risk. Using AI to draft a meeting agenda is very different from using AI to analyze financial data, summarize contracts, or support audit documentation.

Focus first on AI use that touches:

• Financial reporting

• Accounting records

• Payroll

• Customer, patient, or employee data

• Compliance requirements

• Management review controls

• Audit support

• Sensitive business information

Create or Update an AI Use Policy

A written policy helps employees understand what is allowed, what is prohibited, and when approval is required.

Require Human Review

AI-generated work should be reviewed by someone qualified to evaluate the output. The review should be documented when the work affects accounting, reporting, controls, or compliance.

Maintain Documentation

If AI is used in a significant accounting or audit-related process, document the tool, inputs, outputs, review, and final conclusion.

Evaluate Vendors

If accounting or operational software includes AI features, ask vendors about data use, security, access controls, model training, and available SOC reports or other assurance documentation.

Train Your Team

Employees should understand both the benefits and risks of AI. Training should include confidentiality, data security, accuracy, documentation, and review expectations.

Why This Matters Before an Audit

Auditors may not ask every company about AI today, but AI use can affect areas auditors already care about, including:

• Internal controls

• Financial reporting

• Data integrity

• Estimates and judgments

• Information produced by the entity

• Vendor and service organization controls

• Cybersecurity and access risk

• Documentation quality

• Compliance requirements

If AI is part of your accounting process, management should be prepared to explain how it is used and how the related risks are controlled.

Audit readiness is not just about having schedules prepared. It is about having processes, controls, and documentation that support the numbers.

Questions Management Should Ask

Before your next audit, consider asking:

• Are we using AI in accounting, finance, reporting, or compliance?

• Do we know which AI tools employees are using?

• Have we approved those tools?

• Are employees entering sensitive data?

• Are AI outputs reviewed before being used?

• Do we document AI-assisted work?

• Are AI features built into our accounting or payroll software?

• Have we reviewed vendor security and data practices?

• Do our policies address AI use?

• Could we explain our AI process to auditors?

If the answer to several of these questions is “no” or “not sure,” it may be time to review

your AI governance and controls.

Helpful Resources

For organizations that want to learn more about AI risk, cybersecurity, and audit-related considerations, these resources may be helpful:

• NIST AI Risk Management Framework — A framework for identifying, assessing, and managing AI-related risks.

• NIST Artificial Intelligence Risk Management Framework Playbook — Practical questions and suggested actions for applying the AI Risk Management Framework.

• CISA Artificial Intelligence — Cybersecurity and infrastructure security guidance related to artificial intelligence.

• AICPA & CIMA: Artificial Intelligence in Audit and Assurance — Resources related to AI, audit, assurance, and the accounting profession.

• AICPA & CIMA: Audit Data Analytics — Guidance and resources on data analytics in audit and assurance work.

• GAO: Artificial Intelligence — Government Accountability Office resources on AI oversight, accountability, and risk.

These resources can help organizations better understand AI governance, documentation, cybersecurity, and risk management expectations.

Final Thoughts

AI is changing how businesses work, including accounting and finance. It can improve efficiency, support analysis, and help teams manage large amounts of information.

But AI also introduces risk.

Companies should know where AI is being used, what data is involved, who reviews the output, and how the process is documented. The organizations that handle AI best will be the ones that combine technology with strong controls, clear policies, and sound professional judgment.

If your company is using AI in accounting, finance, compliance, or audit support, now is the time to review the risks before they become audit issues.

Contact our office if you would like help assessing AI-related accounting risk, strengthening controls, or preparing for your next audit.