AI tax filing sounds easy — until it leaves you owing the IRS thousands of dollars

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Using AI to file your taxes might feel like a smart shortcut.It isn’t.

With the April 15 deadline approaching, millions of Americans are looking for ways to make tax season less painful, and some AI CEOs are promoting their tools as a helpful solution.

AI chatbots, including ChatGPT, Claude and Grok, explain tax rules, flag deductions and even help assemble a tax return in mere minutes.These tools are seductive, given how frustrating the endless stacks of IRS forms can be.

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But don’t be fooled:doing your taxeswith AI puts you at serious financial risk.That is why the IRS is currently cautioning taxpayers against it for this purpose.

AI is genuinely useful for helping people understand the taxation process.Ask an AI chatbot to explain the difference between a credit and a deduction and it will usually give you a clear answer.Ask it to summarize a rule and it can save you time.

Butfiling a tax returnis not just about sounding informed.It’s about making sure all the information you input is correct.

AI tools might give you useful “suggestions” or even craft certain forms for you.However, have they done it competently and in accordance with the law?This is where things get tricky.AI tools must always be used with a strong degree of expert oversight, and unless you are a tax expert, you are at risk of making incorrect or even fraudulent filings.

Using AI for tax preparation fails across all five core principles of the TRACE framework for safe AI use: task exposure (mistakes can have serious consequences), response tolerance (tax filing requires precision, not “good enough” answers), audit feasibility (most users lack the expertise to verify outputs), confabulation risk (AI can generate incorrect information), and environmental sensitivity (sensitive financial data may be exposed).

Consumer AI tools are not built to guarantee accuracy.They generate answers that read well and sound convincing, but that’s very different from applying a complex tax code correctly, line by line, based on individual circumstances.

A recent study showed how wide that gap can be.When tested on standard tax scenarios, leading AI systems routinely made big mistakes — misapplying thresholds, miscalculating liabilities, and incorrectly determining eligibility for common credits that millions of taxpayers depend on and claim for themselves every year.

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According to the study, “Our experiment shows that state-of-the-art models succeed in calculating less than a third of federal income tax returns even on this simplified sample set.” Would you trust an accountant who had a 30% chance of filing your tax return correctly?

Often the tax errors made by AI aren’t small.Another study found AI turning in results that were off by thousands of dollars.Again, would you ever tolerate that from an accountant?

The danger isn’t just that AI gets things wrong.It’s that it gets things wrong with confidence.

A chatbot doesn’t hesitate or flag uncertainty.It delivers a polished answer that feels authoritative, even when it’s incorrect.That creates a false sense of security at exactly the moment when precision matters most.

Unlike a tax professional, an AI doesn’t bear any responsibility if you get penalized by the IRS.It’s very likely you’ll incur steep penalties if your taxes are inaccurate — and claiming “the robot ate my homework” is no excuse.Moreover, even if you are lucky enough to not be caught by the IRS this time around, remember that later years’ tax preparation uses previous years’ as a blueprint, and so these errors can propagate into the future.

There’s also the matter of what you’re revealing to the AI.To get meaningful tax help from an AI tool, you’re often prompted to share highly sensitive personal and financial data — income details, household information, addresses and sometimes full tax documents.That’s the same information experts constantly warn people to protect so their identities aren’t stolen.

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Once that data is entered, most users have no idea how it’s handled.How long is it stored?Who can access it?Could it be used to improve future systems?The answers are not always clear and the level of transparency varies across platforms.

Hemant K.Bhargava is a Distinguished Professor at UC Davis Graduate School of Management and Director for the Center for Analytics and Technology in Society.