How to Measure AI ROI: 3 Lessons from Legal Leaders

Your AI tool saves 10 hours of work.

But what are those hours actually worth?

As organizations invest in AI, demonstrating a return is becoming increasingly important. Productivity gains are relatively easy to point to. Connecting those gains to meaningful business outcomes is more complicated.

During Apertera’s recent webinar, From Investment to Impact: Measuring the ROI of AI, leaders with experience at Meta, American Express, and Harbor explored what organizations should be measuring, where traditional ROI calculations fall short, and how to demonstrate the value of AI investments.

Watch the webinar below to earn 1 hour of Substantive Content and explore the three key takeaways from the discussion.

Table of Contents

Define AI ROI Based on Business Outcomes

How do you measure the return on an investment when the value looks different depending on what you’re trying to achieve?

According to Mike Haven, Global Head of Legal Operations at Meta, legal departments can evaluate AI ROI through four distinct categories:

• Deflecting work: Enabling business teams to handle routine legal requests through self-service.
• Keeping work in-house: Reducing reliance on outside counsel by handling more work internally.
• Absorbing demand: Managing growing workloads without proportionally increasing resources.
• Creating new capabilities: Using AI to accomplish work that previously wasn’t possible or practical.

Each creates value in a different way. And each requires a different measure of success.

For example, reducing outside counsel spending can produce measurable financial savings. Handling more work with the same team creates capacity, but doesn’t necessarily reduce costs.

The takeaway? Before calculating AI ROI, organizations need to define what success looks like and choose metrics that reflect those objectives.

Measure What Happens to the Time AI Saves

If AI saves an employee 10 hours a week, does that mean the organization has saved 10 hours’ worth of money?

Not necessarily.

Kimberly Bell, Advisor at Latitude Legal and formerly of American Express, emphasized that productivity gains don’t automatically translate into financial savings.

The distinction matters. An employee who completes a task in half the time is still being paid the same salary. The financial benefit depends on what happens with that additional capacity.

Does the team take on more work without increasing headcount? Respond to requests faster? Spend more time on complex matters that require professional judgment?

Those outcomes create value, but they aren’t all measured the same way.

And that raises an important question for organizations investing in AI: Where is the time saved actually going?

The takeaway: Tracking hours saved is a starting point. Demonstrating AI ROI requires understanding how that time is being used and what value it creates for the business.

Account for the Full Cost of Your AI Investment

The price of an AI tool is only part of what an organization pays to use it.

Implementation takes time. Employees need training. Systems require ongoing maintenance and oversight. And AI-generated work still needs to be checked.

During the webinar, Zena Applebaum, SVP, Head of Marketing at Harbor, highlighted what she called the ‘verification tax’: the time and resources required to review AI-generated outputs for accuracy.

That cost can be easy to overlook.

A tool might generate a document in minutes, but if a professional spends significant time reviewing and correcting it, the productivity gain may be smaller than expected.

Mike Haven also emphasized the importance of establishing reliable baselines before measuring results. Without knowing what a process cost before AI was introduced, it’s difficult to demonstrate meaningful improvements or avoid counting the same benefits twice.

For organizations evaluating AI ROI, the calculation needs to account for the full investment, including implementation, training, governance, verification, and ongoing costs.

The takeaway: A credible ROI calculation considers both the value AI creates and the resources required to deliver it.

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Frequently Asked Questions

1. How do you measure the ROI of an AI investment?
Start by defining the business outcomes you want to achieve. AI ROI can be measured through cost savings, increased capacity, faster workflows, or new capabilities. Establish a baseline before implementation and select KPIs that reflect those objectives.

2. Does time saved by AI count as financial savings?
Not automatically. Time saved creates additional capacity, but financial savings depend on how that capacity is used. For example, an organization might reduce outsourcing costs, avoid additional hiring, or handle more work with existing resources.

3. What costs should be included when calculating AI ROI?
A comprehensive AI ROI calculation should include licensing, implementation, employee training, governance, ongoing maintenance, and the cost of verifying AI-generated work. Accounting for these expenses provides a more accurate picture of the return on your AI investment.