BofA Securities 2026 Information & Business Services Conference
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Thomson Reuters (TRI) BofA Securities 2026 Information & Business Services Conference summary

Event summary combining transcript, slides, and related documents.

Logotype for Thomson Reuters Corporation

BofA Securities 2026 Information & Business Services Conference summary

9 Jul, 2026

AI strategy and differentiation

  • Emphasizes the need for fiduciary-grade AI for legal, tax, and audit professionals, focusing on deterministic solutions validated by domain experts.

  • Differentiation is based on proprietary data, thousands of domain experts, strict data privacy, and robust customer support.

  • Guarantees customer data privacy, ensuring inputs are not used to train AI outputs, addressing a key concern for professional users.

  • Integrated support network allows users to access expert help at any time, enhancing trust and reliability.

  • Upcoming CoCounsel release is in alpha, moving to beta on April 20th, with general release expected in summer.

Product innovation and market expansion

  • CoCounsel is positioned to strengthen presence in litigation and law firms while expanding into transactional and corporate legal segments.

  • Recent adoption by major clients, such as Microsoft's general counsel group, signals growth in corporate legal markets.

  • Legal business is experiencing 9% organic growth, driven by the full portfolio including CoCounsel, Westlaw Advantage, and Practical Law.

  • Westlaw Advantage, launched in August 2025, is performing strongly, contributing to legal segment growth.

  • Plans to provide more detailed segment disclosure, especially for legal professionals excluding government clients.

AI partnerships and technology development

  • Maintains a model-agnostic approach, using top-performing models like Claude, ChatGPT, and Gemini, and has developed an in-house legal-specific LLM called Thomson.

  • In-house model is outperforming foundation models for specific legal tasks, providing cost and performance advantages.

  • Model-agnostic strategy mitigates supply chain risks, allowing flexibility if vendor restrictions arise.

  • Differentiates from general-purpose AI by focusing on content, expert validation, privacy, and support.

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