Apr 17, 2025 | AI

Recently, Thomson Reuters leaders held a joint panel discussion with Deloitte, uncovering strategic approaches to implementing generative AI across organizations—emphasizing business-driven objectives, proactive governance frameworks, custom tool development, and human-centered adoption strategies that transform AI potential into tangible business performance. Below were a few key insights shared from the discussion:

1. Gen AI as a strategic business tool
   Audrey Ancion, Partner, AI Institute Canada Leader, Deloitte, discusses how generative AI should be viewed as a value-creating business tool rather than just a technology trend. She emphasizes an “insight-driven approach” at Deloitte, which balances data and technology with people, strategy, and process considerations. Audrey reinforces that successful AI implementation begins with clear business objectives rather than technology experimentation. Organizations should first identify the specific business needs or opportunities they want to address, and then select the appropriate technological solution—not the other way around.

    

2. Proactive AI Governance in a Rapidly Evolving Regulatory Landscape
   David Wong, Chief Product Officer, Thomson Reuters, outlines the forward-thinking approach to AI governance. He describes how Thomson Reuters is not just focusing on current compliance requirements, but actively preparing for future regulations. Key elements of the strategy include implementing a comprehensive AI model governance process, maintaining a model registry, establishing rigorous asset management practices, and updating customer data privacy policies. David emphasized a dual focus: ensuring full compliance with existing regulations while building flexible systems and infrastructure that can quickly adapt to new requirements as they emerge in this fast-changing regulatory environment.

    

3. Leveraging AI Tools Across the Product Development Ecosystem
   David Wong discusses how AI tools like GitHub Copilot are enhancing their engineering teams’ productivity and product quality. He shares that Thomson Reuters is now exploring AI solutions for non-engineering roles including editors, content experts, and designers. He notes this initiative is still developing, but early successes have come from adopting vendor-created generative AI products that adapt large language models for specific business functions.

    

4. Building Custom AI Tools for Editorial Excellence
   David Wong highlights Thomson Reuters strategic investment in proprietary AI technology for editorial teams. He explains that while they leverage vendor solutions where possible, their specialized legal editorial needs require custom-built tools. David reveals they’ve launched six internal development projects this year, led by Leanne Blanchfield and editorial teams, to create Thomson Reuters-owned AI software specifically designed to enhance editor efficiency, speed, and accuracy—ultimately improving customer service.
   

    

5. The “4 Ts” of Human-Centered AI Adoption at Thomson Reuters
   Chief People Officer Mary Alice Vuicic outlines Thomson Reuters’ “4Ts” framework for successful AI adoption across the organization. She emphasizes that human adoption—not technology—presents the greatest challenge. The framework includes:
   –  Tone from the top, with CEO Steve Hasker championing AI as critical for the company, customers, and individual career resilience;
   – Training, with accessible programs for both technical and non-technical staff;
   – Tools, providing all employees access to Open Arena (Thomson Reuters internal AI platform) with four leading language models; and,
   – Time to experiment, encouraging daily AI use to build habits.
   Mary Alice reinforces that hands-on experience significantly reduces employee anxiety about AI, making it more accessible than previous technological transformations.