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Episode

AI Agents in Legal Tech - David Wong Thomson Reuters on Responsible AI | EP 127

Podcast
AI Agents Podcast
Published
Mar 25, 2026
Duration seconds
2918
Processing state
processed
Canonical source
https://podcasters.spotify.com/pod/show/ai-agents-podcast/episodes/AI-Agents-in-Legal-Tech---David-Wong-Thomson-Reuters-on-Responsible-AI--EP-127-e3gd1lc
Audio
https://anchor.fm/s/fe2628e4/podcast/play/116868204/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-2-25%2F420744647-44100-2-5c6db5e4ee4bf.mp3
JSON
/v1/public/podcasts/ai-agents-podcast/episodes/ai-agents-in-legal-tech-david-wong-thomson-reuters-on-responsible-ai-ep-127
Markdown
/podcast/ai-agents-podcast/ai-agents-in-legal-tech-david-wong-thomson-reuters-on-responsible-ai-ep-127.md

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Summary

Thomson Reuters is transforming professional services by moving beyond news into AI-driven software for legal, tax, and audit workflows. The discussion explores how agentic frameworks solve the 'math problem' in tax by using AI to orchestrate specialized tools rather than relying on raw LLM computation.

Topics

  • AI Agents
  • Legal Tech
  • Tax Automation
  • Thomson Reuters
  • Agentic Workflows
  • Model Context Protocol
  • Professional Services
  • Enterprise AI

Highlights

  • Main idea: AI agents in professional services act as orchestrators that use specialized tools (like tax calculators) rather than performing complex math internally
  • Practical takeaway: Successful AI implementation requires both 'book smarts' (authoritative reference data) and 'street smarts' (expert human judgment)
  • Failure mode: Relying on LLMs to perform direct computation in tax or legal contexts leads to inaccuracies; the solution is API-driven tool use
  • Main idea: The Model Context Protocol (MCP) serves as essential 'plumbing' to connect AI agents to disparate professional software and datasets
  • Future outlook: AI agents will enable flatter organizational structures, allowing smaller teams to manage high-volume workloads through automated 'army' of agents

Chapters

  1. 1:00 Introduction to David Wong: A brief introduction to David Wong, Chief Product Officer at Thomson Reuters, and his background in B2B software.
  2. 2:54 The Thomson Reuters Ecosystem: Understanding how Thomson Reuters operates primarily as a software and research powerhouse for professionals rather than just a news agency.
  3. 8:40 Early GPT-3 Testing in Legal: Reflections on the 2020 era of testing GPT-3 for legal research and the realization of AI's potential impact.
  4. 16:20 Agentic Solutions for Tax: How agentic frameworks solve the reliability issues in tax preparation by using AI to interface with existing tax engines and APIs.
  5. 26:55 Teaching AI to Use Tools: The shift from teaching LLMs to calculate to teaching them how to use calculators and specialized software via APIs.
  6. 37:45 The Future of Team Structures: How AI agents will flatten professional hierarchies by enabling smaller, highly efficient teams to handle massive workloads.
  7. 41:20 MCP and System Interoperability: The role of the Model Context Protocol (MCP) in expanding the capabilities of AI agents by connecting them to external data and applications.