AI Can Handle the Tax Code. What Still Needs a Human?

AI Can Handle the Tax Code. What Still Needs a Human?

From The Tech Trek by Elevano

May 15, 2026 · 25 min · Episode 667

About this episode

David Kang discusses the role of AI in tax workflows and the importance of human involvement in high-stakes environments.

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…

People in this episode

Guest: David Kang

Topics covered

  • AI in tax
  • human judgment
  • automation
  • trust in AI
  • language models
  • tax workflows

Keywords

  • AI
  • tax code
  • human escalation
  • automation
  • trust
  • language models
  • workflow

Mentioned in this episode

Organizations: Keeper

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