Trust, But Verify: Why Managing AI Agents Starts with Healthy Skepticism
Artificial intelligence has arrived in tax due diligence with remarkable speed. Tasks that once took hours can now be completed in minutes. AI agents can review documents, identify potential tax issues, summarise legislation and even draft reports with impressive fluency. It's no surprise that many firms are exploring how these tools can increase efficiency and free up specialists to focus on higher-value work.
There is, however, one habit that consistently separates those who use AI effectively from those who are most likely to be caught out.
Assume the answer is wrong.
Not because AI is unreliable. Not because it isn't useful. The most effective way to manage an AI agent is to begin with the assumption that every response deserves to be challenged, that somewhere within it there may be an omission, an assumption or an inaccuracy.
This can feel counterintuitive. After all, AI writes with extraordinary confidence. It rarely hesitates. It doesn't tell you it's having an off day. It presents conclusions in polished prose that sound authoritative, even when they are incomplete or occasionally incorrect.
Humans are naturally inclined to trust confidence. In meetings, the person who speaks most decisively often carries the room. AI exploits exactly the same cognitive bias, without intending to. The danger is not that AI makes mistakes. The danger is that it makes mistakes convincingly. In tax due diligence, that distinction matters.
Whether reviewing historic tax positions, analysing transaction structures or identifying potential exposures, small inaccuracies can have significant commercial consequences. A missed assumption, an outdated interpretation or a subtle misunderstanding of context can easily make its way into a report if nobody stops to question it.
The best AI users therefore don't treat the agent like an expert. They treat it like a very capable graduate analyst.
It works quickly. It can digest huge volumes of information. It often produces an excellent first draft. But every conclusion still deserves scrutiny. Every reference should be checked. Every recommendation should be challenged.
The objective is not to prove the AI wrong. It is to ensure that important decisions are built on evidence rather than confidence.
Rather than asking, 'Is this right?', experienced practitioners often ask, 'What would make this wrong?' That single shift in thinking changes everything.
It encourages professionals to validate sources, test assumptions and look for exceptions. It turns AI from an answer machine into a thinking partner. Instead of replacing critical judgement, it amplifies it.
Ironically, this mindset often leads to greater trust in AI over time. When professionals understand where the technology excels, and where it can occasionally stumble, they learn when to rely on it and when to investigate further. Confidence becomes informed rather than automatic.
As AI agents become increasingly autonomous, managing them will become a professional skill in its own right. The role of the tax specialist will evolve from producing every answer manually to directing, reviewing and quality-assuring the work produced by intelligent systems.
In many ways, this mirrors how experienced managers oversee junior team members. The expectation is not perfection. The expectation is thoughtful supervision.
Confidence should never be confused with accuracy.
The most successful tax professionals won't be those who blindly trust AI, nor those who refuse to use it. They'll be the ones who remain professionally sceptical, ask one more question than everyone else, and remember that while AI can generate answers at remarkable speed, judgement is still very much a human responsibility.
If you’d like to see how TAINA can simplify and streamline your CARF and CRS compliance journey, we’d be delighted to request a demo.
To stay up to date with our latest insights on tax compliance, automation and regulatory change, sign up for our industry newsletter.
