Episode
AI Can Handle the Tax Code. What Still Needs a Human?
- Podcast
- The Tech Trek
- Published
- May 15, 2026
- Duration seconds
- 1483
- Processing state
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Summary
Tax is one of the hardest places to earn trust with AI. The work is complex, the stakes are personal, and being mostly right is not good enough. In this episode of The Tech Trek, David Kang, founder and CEO of Keeper, explains how his team is applying AI to tax workflows without pretending humans disappear from the process. He breaks down why tax is such a strong fit for language models, where AI can reduce manual review, how Keeper decides when a case needs human escalation, and why the best products may feel less like autonomous agents and more like systems that make experts sharper. Key Takeaways • AI is most valuable when it removes repetitive work while preserving human judgment where risk is highest. • High trust products need clear escalation logic, especially when edge cases drive most of the anxiety. • Tax is a strong fit for AI because much of the work involves language, rules, validation, and workflow routing. • The smartest AI adoption often starts with bounded operational tasks before moving into more domain specific decisions. • Consumer trust in AI can change quickly, but messaging still matters when the product sits inside sensitive workflows. Highlights 00:34 Where Keeper fits for people who have outgrown DIY tax software but do not need a traditional personal accountant. 02:27 Why tax may be one of the more practical use cases for AI, even in a high stakes environment. 07:15 The accounting talent shortage, what automation may replace, and how roles could shift. 10:55 How Keeper uses AI before professional review to flag possible issues and optimization opportunities. 13:51 Why the company moved from keeping AI in the background to talking about it more directly. 17:58 How Keeper separates the routine parts of a tax return from the parts that need expe…