Accounting ethics in the age of AI

Artificial intelligence is no longer a future issue for the accounting profession — it has moved from “someday” to “right now” faster than many expected. Whether it’s automating routine tasks, analyzing massive datasets, or drafting reports, AI tools are quickly becoming part of daily life for accountants in both business and public practice.

Despite the speed at which AI is changing the ways accountants and finance professionals work, the AICPA Code of Professional Conduct still provides clear, enduring guidance. AICPA members’ core responsibilities — competence, due care, confidentiality, and independence — don’t disappear just because new technology is involved. What changes is the need to think more intentionally about how you use AI and why you’re using it.

This isn’t about discouraging AI use. Far from it. It’s about using the technology in ways that support your work without creating new ethical risks.

Professional judgment can’t be delegated to AI

One of the most important concepts in responsible AI use is “human in the loop.” AI can generate impressive output quickly, but it can also sound confident when it’s wrong, reflect bias, or miss nuance that only the human mind could catch.

This is where professional judgment comes in. CPAs are trained to apply skepticism, experience, and context — qualities no algorithm can fully replicate.

When reviewing AI output, ask yourself: Does this make sense given everything I know? Are there contradictions? What assumptions is the system making?

It helps to watch for a few human habits that AI can amplify:

• Automation bias. Trusting the machine’s answer even when your own reasoning or other evidence suggests caution.
• Overconfidence bias. Treating AI as infallible.
• Anchoring bias. Latching onto the first piece of information the tool provides and letting it color everything that follows.

The best safeguard is simple: Stay actively involved. Treat AI as an assistant, not a substitute for your own critical thinking.

Competence and due care are crucial

The code’s “General Standards Rule” (ET secs. 1.300.001 and 2.300.001) hasn’t changed. You must undertake only services you can complete competently and with due professional care. Before relying on AI for a task, consider whether you (or your team) truly understand its strengths, limitations, and risks in that specific context.

Gaining that competence might mean additional research, training, testing the tool on non-sensitive data first, or consulting colleagues with relevant experience. Whether the AI was built in-house or comes from a third-party provider, the responsibility for the final work product rests with you.

AI can create confidentiality risks quickly

Confidentiality risk often starts with the data users enter into the AI tool. Some publicly available generative AI tools employ user inputs to train future models. That means sensitive employer or client data that is entered could potentially resurface elsewhere. Members in business need to be especially careful not to inadvertently disclose confidential employer information.

Specific risks also exist for members in public practice. They have the added layer of the “Confidential Client Information Rule” (ET sec. 1.700.001). Before pasting client data into any AI system, stop and ask: Is this confidential client information? Is consent required, and if so, has the client specifically consented? Could this use result in disclosure to third parties? When consent is required, make sure your client understands what information may be used, why it’s being used, and who may have access to it.

That’s one reason many firms now steer employees toward approved AI tools with clear data-handling protections.

AI services can raise independence concerns for attest clients

For members in public practice, providing AI-related nonattest services, such as developing or hosting an AI system for an attest client, can raise independence concerns. The existing rules on nonattest services and information systems still apply.

In situations the code doesn’t explicitly address, fall back on the conceptual framework: Identify threats, evaluate their significance, and apply safeguards as needed. When required, document your analysis. Transparency with clients about when and how AI is being used can strengthen trust.

Make ethical AI use part of everyday practice

AI offers tremendous opportunities to work more efficiently and deliver deeper insights. But technology alone doesn’t create ethical outcomes — people do. The most successful organizations will treat AI ethics the same way they treat all ethics: not as a checklist, but as part of an ongoing conversation about doing the right thing, even when no one is watching. (Also see, “Making the Right Choice When No One Is Watching,” JofA, June 8, 2026).

That means modeling thoughtful AI use, encouraging open discussion about its risks and benefits, and continually reinforcing that professional judgment and ethical responsibilities remain at the center of everything we do.

For a deeper dive, the AICPA Online Ethics Library has an Ethics Staff Insights article, “AI Through an Ethics Lens,” that goes further into this topic with practical examples, additional scenarios, and resources, including factors to consider when using the output of technology (see nonauthoritative Q&A section 400.02).

In the meantime, remember: AI can be a powerful tool, but the profession’s ethical foundation — and your responsibility to uphold it — remains distinctly human.

— Kelly D. Mullins is the communications manager for the AICPA Professional Ethics Division. To comment on this article or to suggest an idea for another article, contact Jeff Drew at Jeff.Drew@aicpa-cima.com.