AI in Tax Preparation: Balancing Innovation and Accountability.

Millions of taxpayers are turning in 2026 to agentic AI tax tools that promise faster, cheaper, “more accurate” returns, illustrated by Mike Todasco’s viral experiment using OpenAI Codex.

But testing by the New York Times and the TaxCalcBench benchmark shows major reliability gaps: leading models often miss small details and fail strict field-by-field accuracy, while even advanced multi-agent systems fall short of full automation.

Despite heavy marketing, Intuit has acknowledged generative AI performs poorly at math and avoids using it for TurboTax calculations.

The core risk is accountability: taxpayers remain legally responsible for errors, while AI tools sit in a regulatory gap with no professional liability, standards, or required disclosures. Privacy and discoverability risks also rise after a 2026 ruling in U.S. v. Heppner denying privilege for AI-generated legal work.

The IRS warns against AI reliance yet uses AI internally, contrasting with the EU AI Act’s high-risk compliance framework.