The reliability problem. AI systems are as reliable as the data on which they’re trained. That means if there is a flaw, AI will confidently analyze incomplete, biased, or incorrectly interpreted data, potentially amplifying mistakes.
When most businesses seek a research and development credit, for example, the most they have is a list of projects. They rarely have data on who worked on the project, the hours spent, or what their process of experimentation was like. It takes a seasoned tax professional and industry knowledge to ask the questions necessary to build a narrative to satisfy the IRS.
With just a list of projects, AI has no context for qualification, so it gives a binary result; either everything qualifies or nothing does. That’s not a risk anyone should be taking.
The hallucination problem. AI “hallucinates,” offering plausible but incorrect information with such confidence that it may make one question oneself. This can be incredibly problematic when preparing taxes.
This is why professional tax practitioners will not pass on a tax study or filing without double checking if AI was used at any point during the process, even for mere arithmetic.
OpenAI, the industry standard for AI, has released two studies: one showing that it is a mathematical certainty that large language models will hallucinate, and the second showing that it is a mathematical certainty that such models will deliberately lie to tell users what they want to hear.
It’s no surprise then that OpenAI updated its policy to explicitly prohibit people from using their services for “provision of tailored advice that requires a license, such as legal or medical advice, without appropriate involvement by a licensed professional.” If this is what the industry leader on AI is saying, how could you take anyone else seriously?
The courtroom problem. AI-generated information isn’t legally reliable. It can’t take an oath because it doesn’t understand what a lie is. It can’t testify because it doesn’t really know how it’s generating information, and AI-generated content can’t be admitted as evidence without proper foundation and authentication.
The fundamental problem tax practitioners using AI face is how to make its output legally defensible. If they can’t, using AI for any complex tax, audit, or compliance-related task is futile.
The evolutionary problem. Tax laws, rules, and regulations change year over year, administration to administration. No matter how fast one trains the AI system, it will always be a few steps away from catching the latest standards.
If a tax practitioner is over-reliant on AI and hasn’t kept up with the recent developments, it will expose both them and their clients to significant risk.