Insights

The rise of generative AI tools like ChatGPT has sparked intense curiosity — and no shortage of concern — among accounting professionals. Can AI really help draft technical memos? Summarize new FASB updates? Support financial reporting workflows? The short answer: yes — with limits. AI is quickly proving itself to be an invaluable research assistant. But it is not, and should not be mistaken for, a licensed accountant.

Where AI Adds Real Value

Today’s generative AI systems can assist in preparing a wide range of language-heavy accounting deliverables:

- Drafting footnote disclosures from trial balances

- Writing policy memos and internal documentation

- Summarizing new IFRS or GAAP updates in plain English

- Editing technical text for tone, grammar, or clarity

Think of it as having a tireless junior staffer who’s never too busy to start the first draft. For example, we’ve seen AI turn a trial balance and a brief accounting policy note into a draft footnote disclosure in seconds. In the hands of a CPA, this speeds up early-stage work, allowing professionals to focus on review, analysis, and client service.

Efficiency Gains Backed by Data

Recent surveys support this trend. In one industry poll, 71% of accounting firms reported that AI-powered tools — including large language models — are becoming essential to serving clients efficiently and competitively. Firms using AI for drafting, summarizing, or reviewing documents say it streamlines busy-season workflows and reduces time spent on repetitive tasks, like rewriting financial statement footnotes or reviewing lengthy contract language for accounting treatment clues.

But AI Is a Poor Substitute for Judgment

_While AI is fast and fluent, it’s not infallible._ As the AICPA has rightly cautioned, generative AI lacks context, skepticism, and technical nuance. It may write clearly, but it doesn’t “understand” accounting. It can’t reason through grey areas, assess control risks, or interpret how to apply principles-based standards in real-world scenarios. For example, an AI might correctly identify that ASC 842 governs lease accounting — but misapply its rules in a scenario involving variable lease payments or renewal options. The output may _sound_ authoritative, but lack technical accuracy.

Beware of AI “Hallucinations”

Another critical risk is hallucination — the tendency of AI tools to invent plausible but incorrect facts. We’ve seen examples where AI-generated accounting memos referenced non-existent FASB guidance, misquoted materiality thresholds, or applied obsolete standards. That’s why professional oversight is non-negotiable. Any AI-generated content should be treated like a junior staffer’s draft: reviewed line by line, validated against source guidance, and approved by a qualified accountant. Some firms are even formalizing this with policies that require staff to flag when AI was used in preparing a deliverable — ensuring proper scrutiny and accountability.

When to Use AI (and When Not To)

Here’s a useful rule of thumb:Appropriate AI Use Cases

- Summarizing long or complex guidance

- Drafting memos or disclosures from templates or structured data

- Editing for tone, grammar, or structure

- Comparing historical memos for consistency

Tasks That Require Human Judgment

- Drawing conclusions on complex accounting treatments

- Assessing compliance with nuanced standards

- Making policy decisions based on incomplete data

- Any scenario with legal, audit, or reputational risk

As one expert put it: _“Generative AI may appear confident, but indiscriminate reliance on its output without human skepticism can lead to serious errors.”_

Best Practices for Safe AI Use in Accounting

1.Start with a clear prompt and use structured inputs.

2.Review every AI-generated draft thoroughly.

3.Cross-check technical references against authoritative sources.

4.Flag use of AI where required by firm policy.

5.Treat AI as a support tool, not a subject-matter expert.

Closing Thought

AI is changing how accountants work — not what accountants are for.When used properly, AI accelerates routine research and documentation. It creates space for deeper judgment, client advisory, and value-added work. But guardrails are essential. Judgment, accountability, and ethics remain squarely human responsibilities