16-17 June 2027 – London, InterContinental O2 | Magazine

LegalTech Diaries Volume 19

Norie Campbell

CLO
Thomson Reuters

LegalTech Diaries Volume 19

Norie Campbell

CLO
Thomson Reuters

You joined Thomson Reuters at the exact moment it acquired Casetext and CoCounsel. What was it like stepping into a legal department that was about to become the test bed for the company’s own AI products?

I remember thinking “could everyone just take a pause for 6 months and let me catch up?”. But, of course that wasn’t going to happen and the General Counsel’s Office at Thomson Reuters has been operating in a dynamic, competitive world ever since. I think what we have done really well is seized the synergy of both learning about AI as a legal topic to manage for our business and as a game-changer for our practice of law in the department. Every time we are using our tool, CoCounsel, to answer a question or draft a document, we are learning more about how AI works and that is making us better lawyers and advisors to our business. It is exciting that some of the best AI tools in the world are being created for lawyers and it provides a unique opportunity for lawyers to better understand the functionality and usefulness of AI.

You’ve argued that the “more for less” era is over and that legal teams need to move beyond efficiency metrics to demonstrate business value. What does a legal team measuring business value, rather than efficiency, actually look like in practice?

This is something I am very passionate about. Of course you must gain efficiencies from using AI—that is table stakes. But in our General Counsel’s Office we are measuring success across other metrics. For example, we evaluate ourselves on how well we protect the company and we have been working hard to have meaningful KPIs to measure our important role in protecting the organization from legal risk. Here is a spot where we are having a real breakthrough– Our tools make it easy not only to have a playbook but also to use that playbook to measure “drift” from our gold standard. At the heart of that drift is often accepting risk. Having efficient visibility into that is a great way to understand where our risk is ratcheting up.
Satisfaction measures are also key, whether that is the legal professionals that work for me, our internal clients across the business and, indeed, our customers. There, we are building a measure that gives us real data on our speed to put the product into the hands of our customers—that really matters.

Your remit spans legal, risk, compliance, privacy, government affairs and social impact. How do you decide where AI adoption should lead across that range, and where it should follow?

We are running a dual-track process—engagement and industrial strength. For engagement, I want everyone on the team to have access to AI that they can use successfully in their work. We are giving them the tools, championing the use cases and providing the training. On the “industrial strength” side, this is about building use cases that are at scale meaning that they apply to many across the team on tasks that take lots of time and are ripe for AI to help. With this two track process, no one is left behind and we are also putting tons of energy into really valuable use cases that can demonstrate strong return on the investment we are making in embedding AI in our work.