To maximize AI training, build ‘habits, not checklists’

Summary

This article addresses the growing gap between AI tool adoption and effective AI workforce training in organizations. The central argument, advanced by Gary Lamach of ELB Learning and Mary Alice Vuicic of Thomson Reuters, is that AI transformation is fundamentally a mindset and culture challenge before it is a technical one. Key evidence drawn from Thomson Reuters' 2025 Future of Professionals report — based on 2,275 professional services employees globally — includes findings that organizations with visible AI strategies are twice as likely to experience revenue growth, that 96% of professionals have basic AI awareness yet 71% lack practical application understanding, and that professionals with strong AI knowledge are 2.8 times more likely to see organizational benefits. Thomson Reuters' own rollout is cited as a case model, featuring a phased 'four T's' framework. The article concludes that sustainable AI readiness requires habit formation through experiential, adaptive, and role-specific learning integrated into daily workflows, rather than one-off training interventions or tool deployment alone.

Strengths and limitations

Strengths: The article draws on a reasonably large-scale dataset (2,275 respondents globally) and provides specific, quantified claims that lend credibility to its core arguments. The Thomson Reuters case study offers a concrete, named organizational example with measurable targets. Limitations: The primary sources are a Thomson Reuters-commissioned report and an executive from a commercial training platform (ELB Learning), creating dual conflicts of interest — one promoting AI adoption services, the other a training product. The $32 billion impact figure is an extrapolation based on current predicted adoption pace, introducing speculative methodology that is not independently verified. The article does not present dissenting research or acknowledge counterarguments to aggressive AI reskilling investment. Lamach's observations are anecdotal and drawn from client engagements, not published research. The piece reads as practitioner advocacy rather than neutral analysis, and the blending of vendor perspectives with research findings risks overstating the strength of the evidence base.

What this implies

The data cited suggests a bifurcating competitive landscape where the presence or absence of a formal AI training strategy correlates with measurable revenue outcomes. The reported knowledge-practice gap — high awareness, low practical competency — points to a structural limitation in how organizations currently approach AI capability building. The emphasis on habit formation over compliance-based training indicates a potential shift in how L&D functions are positioned within AI transformation programs. The scale of projected productivity gains in professional services sectors may accelerate talent expectations around AI tool access, with retention implications noted in the article.

Key points

• Organizations with formal, visible AI strategies are twice as likely to experience revenue growth compared to those with informal adoption approaches, according to Thomson Reuters' 2025 report.
• A significant knowledge gap exists: 96% of professionals report basic AI awareness, but 71% do not feel they have a good understanding of practical AI applications — and those with expert-level knowledge are 2.8 times more likely to see organizational benefits.
• Legal professionals anticipate freeing nearly 240 hours per year through AI adoption, translating to an average annual value of $19,000 per professional and a projected $32 billion combined impact for legal and tax/accounting sectors in the U.S.

What to take away

• Thomson Reuters implemented a phased AI integration model structured around four touchpoints — tone from the top, training at all levels, tools for hands-on experience, and time to experiment — resulting in a target of 100% employee AI usage by end of 2025.
• Experiential learning mechanisms such as secure sandbox environments, where employees can explore AI without risk, are associated with a 1.9 times greater likelihood of employees seeing benefits from AI adoption, per Thomson Reuters research.