The Risks of AI in Finance: What Every Accountant Should Know

AI offers significant productivity benefits for finance professionals — but it also introduces risks that need to be actively managed. Understanding these risks isn't about being anti-AI; it's about using AI responsibly and professionally. Here are the key risks that accountants should be aware of when using AI tools in their work.

Accuracy and Hallucination Risk

The most immediate risk with large language models like ChatGPT and Copilot is that they can produce confident-sounding outputs that are factually wrong. In finance contexts, this is particularly serious — an incorrect accrual figure, a wrong statutory rate, or an inaccurate prior period comparison in a management account can have real consequences. The risk is not that AI is generally unreliable; it's that AI errors can be subtle and presented with apparent confidence.

Mitigation: Treat all AI-generated financial outputs as first drafts requiring professional review. Never submit AI-generated numbers without verification against source data.

Data Privacy and Confidentiality

Finance professionals work with highly sensitive data: unpublished financial results, salary information, M&A details, and customer financial data. Inputting this information into public AI tools (like the free tier of ChatGPT) raises serious data privacy concerns. The information may be used to train future models or stored by the provider.

Mitigation: Use enterprise versions of AI tools with appropriate data processing agreements, and follow your organisation's data governance policy on what information can be shared with AI systems. If in doubt, anonymise or remove sensitive data before using AI assistance.

Overreliance and Professional Judgement

As AI tools become more capable, there is a risk that finance professionals gradually defer to AI outputs without applying appropriate professional judgement. This is a concern for audit quality, management reporting integrity, and regulatory compliance. Professional standards require accountants to exercise independent judgement — AI can inform and assist that judgement, but cannot replace it.

Mitigation: Establish a clear principle that AI is a tool to support professional decision-making, not a substitute for it. Document your review process when AI is used in preparing financial outputs.

Governance and Auditability

Finance functions in regulated industries need to be able to explain and audit their processes. If AI is used to generate financial narratives or analyses, there needs to be a clear process for reviewing and approving those outputs. Ad-hoc AI use without documented governance creates audit trail gaps.

Mitigation: Develop a simple AI use policy for your finance function that specifies what AI tools can be used for, who reviews AI outputs, and how AI use is documented.

Using AI Responsibly in Finance

The answer to these risks is not to avoid AI — it's to use it with proper professional standards. Finance professionals who understand the risks and build appropriate safeguards will be better positioned than those who either reject AI entirely or use it without proper oversight.

Learnsignal's AI for Finance programme covers responsible AI use alongside practical skills. Join the waitlist today.

Staying Professionally Responsible

The accounting profession has always required professional judgement in the face of uncertainty and incomplete information. AI introduces new forms of uncertainty — outputs that look authoritative but may be wrong, tools that are powerful in some contexts and unreliable in others. The professional response is the same as it has always been: understand your tools, apply critical judgement, document your reasoning, and maintain your own accountability for the work you put your name on. Finance professionals who approach AI with this mindset — curious but critical, open but not credulous — will use it well and avoid its pitfalls. Those who either reject it or adopt it uncritically will both be at a disadvantage.

Structured AI training that specifically addresses professional risk management — like Learnsignal's AI for Finance programme — is one of the most effective ways to develop this mindset deliberately rather than through trial and error.