AI in Professional Services report takeaways for legal teams
AI in Professional Services report takeaways for legal teams
Publish Date: 2026-02-26 09:15:00
Source Domain: legal.thomsonreuters.com
Industry‑specific AI is gaining traction in high‑stakes legal work, such as personal injury litigation.
Highlights
- Generative AI use has surged, shifting professional services from experimentation to measurable impact.
- Legal teams are adopting AI cautiously, balancing speed with ethics, governance, and human oversight.
- Thomson Reuters and Supio demonstrate how industry‑specific AI is strengthening personal injury litigation workflows.
Artificial intelligence (AI) is no longer a future concept for professional services. It’s a present‑day reality. The Thomson Reuters Institute’s 2026 AI in Professional Services Report shows that organizations nearly doubled their use of generative AI in the past year, with more than half of professionals relying on publicly available tools. Industry‑specific and enterprise solutions are also gaining traction as adoption accelerates.
As AI becomes embedded in daily work, firms have moved past the question of whether to use it and toward defining what they expect it to deliver. The focus is now on outcomes that support long‑term business strategy, strengthen client relationships, and create measurable impact beyond efficiency alone. Looking ahead, 77% of professionals expect agentic AI to become central to their workflows by 2030, prompting organizations to explore early use cases.
In legal services, this evolution raises new questions about value, scale, and competitiveness. As one respondent noted, firms cannot keep up with modern‑day corporate demands without changing how legal work is executed.
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The report highlights how quickly AI has been normalized across professional services. More than 80% of organizations report using generative AI weekly, and most professionals believe it will become central to their workflow within the next five years.
With AI adoption now widespread, organizations are moving past the question of whether AI works and toward a more complex challenge: defining what success…
