How can a corporate law department calculate the return on an AI investment?

There is no doubt that an investment in AI or one of the new generative AI (GenAI) tools is no small expense. In the Thomson Reuters Institute’s recent 2025 Report on the State of the US Legal Market, we wrote about the cost of chasing opportunity, and how law firm overhead expenses, particularly those related to technology, continue to grow at a pace that’s notable above the rate of inflation.

For corporate law departments, the cost of an AI-related investment might be on a different scale due to the smaller size of the team, but it is no less daunting given the incessant budgetary pressures that many corporate general counsel (GCs) are under daily. The need to implement an AI-focused strategy along with adopting the tech to support and moving the department toward an AI-driven future is becoming an unavoidable reality for many corporate law departments. Knowing that expense is inevitable, however, does not address the question of how to justify it or calculate the return on that investment (ROI).

Framing the ways we think of ROI

One of the classic measures of ROI is as a multiplier. If a business spends a certain dollar amount on something, they can gauge ROI based on how many multiples of that amount return to the business in gain.

However, this doesn’t really apply to AI in the GCs’ office, for obvious reasons. First and foremost, the GCs’ office typically does not generate revenue for the business, so calculating the revenue generated as a result of an investment in legal tech does not work the same way as it would for a sales or marketing team — but that’s not to say there aren’t ways to calculate return of value to the business.

One potential measure of ROI on new AI tech can be found in its impact on outside counsel spend. If better technology enhances the capacity of the in-house legal team such that there is less need to hire outside counsel, that should factor into the ROI for that specific tech investment.

Of course, there are potential complications here. First, outside counsel rates continue to climb, so even if less work is being sent to outside counsel, total spend on outside counsel may still go up. Second, matter volumes for in-house law departments are increasing nearly across the board and are predicted to continue to do so. As a result, increased matter volumes may exceed even the AI-enhanced capacity of the in-house law department.

How to best respond to these complications is also a matter of framing. Reporting outside counsel spend in raw dollars may not be the best measure of the benefits the in-house team has gained from its AI investment. There are a few other metrics GCs should consider tracking and reporting that might better highlight the benefits the in-house team has gained from AI, including:

• • • ratio of in-house legal matters compared to work sent to outside counsel;
    • increase in total legal matter volume compared to increase in volume sent to outside counsel;
    • percentage increase in matters handled in-house;
    • qualitative measures of the complexity of matters being handled in-house; and
    • savings in projected outside counsel spend at current rates compared to actual outside counsel spend.

The latter measure could actually be quite insightful. It requires multiple data points but speaks the kind of direct financial language in which boards of directors are fluent. Essentially, the GC would need to calculate the amount of work that is now being done by the in-house team as a result of their new-found AI-driven capacity, then calculate what it would have cost to have had outside counsel do that work.

This measure would account for both work that has shifted in-house and away from law firms as well as any new work resulting from the overall increase in matter volume that the in-house team is taking on without involving outside counsel.

Finding creative ways to confront reality

None of this is to suggest that these are the only, or even the best, metrics to meet the challenge of calculating ROI. The more important point is that GCs should be looking creatively in how they think about ROI. Further, the business’s CFO can be an invaluable ally in formulating an approach because the finance team is so often tasked with creating the reporting that other executives and the board rely on when guiding the business. The CFO already speaks the language, and GCs should use them as an interpreter and ally to help shape metrics that tell an effective story for the legal department.

It’s also important to remember that part of the ROI of AI technology is the same as any other technology upgrade. How does the business calculate the ROI on an upgrade to company-provided laptops or phones? How did the business justify making the switch from desktop systems to laptops? While the move to AI is, in many ways, of a different character than past tech upgrades, at its root, what we are talking about in moving to AI-enabled tech is a move to the latest and greatest tech, particularly given its impending ubiquity.

And GCs would be well advised that waiting to learn about and invest in AI until they have the ROI calculation figured out is likely not a safe approach. Nearly 8 out of 10 corporate law departments have reported increasing matter volumes, according to our recent data. At the same time, between 60% and 70% report flat to declining budgets and attorney headcount. This confluence of factors will only ramp up the pressure on GCs to figure out how to handle the increasing demand placed on their departments by the broader businesses they serve.

And while AI provides options to help address these volume and capacity challenges, the results of any investment can and should be tracked and reported to show that the business has not just spent money on new technology for its lawyers but has increased its lawyers’ own ability to contribute to the business’s success.

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