Show me the money! That’s increasingly becoming the mandate for business leaders and their boards as corporations pour massive investment and resources into their AI strategies. In the span of just a year or so, we’ve moved past the point of wowing one another with flashy proofs of concept and impressive-looking experiments. It’s time to start showing results.
For most businesses, however, measuring the concrete benefits of the estimated $2.5 trillion that will be spent on AI this year is easier said than done.
According to new research from Thomson Reuters, even though nearly half (48%) of corporate tax, legal, and risk professionals are currently using AI in their day-to-day work, just 20% of corporations are currently collecting any return on investment (ROI) metrics around that AI usage. Of those that are attempting to quantify the impact of AI, most are focused inwardly on transactional stats like cost savings (77%), employee usage (64%), and employee satisfaction (42%). Just about one-fourth of corporate AI users are measuring client satisfaction (26%) or projected external revenue generation (23%).
These results are not surprising. Time savings and efficiency are often the first place ROI conversations start—and that’s a reasonable entry point. But if the measurement framework stops there, leaders end up with an incomplete view of what AI is (and isn’t) changing. The bigger gap is that many teams aren’t consistently quantifying the outcomes that executives ultimately care about: growth, client impact, talent, speed of execution, and quality/risk.
Updating the Conventional ROI Value Equation
In fact, when I work closely with firms that have embedded AI into multiple core functions, I’ve found that the real value they are getting is much more nuanced than just time-savings or efficiency. The true impact lies in the ability to go deeper, surface insights that were previously out of reach, and deliver higher-value services that would have been cost-prohibitive before AI.
For example, an in-house legal counsel for a multinational corporation recently shared an example of how AI-enabled research capabilities were helping her team model business risks associated with a potential acquisition that would have been impossible using conventional research methods.
That’s not necessarily an efficiency hack or a direct revenue driver, but it could keep her from making a costly misstep that no one would have seen coming if they were conducting due diligence the old- fashioned way. How do you put a value on that?
Five Questions Every Business Leader Needs to Ask Now
Her story and countless others like it prove the point that business leaders really need a new set of metrics for assessing the impact of AI. Based on conversations with hundreds of corporate tax, legal, and risk and compliance teams who have been integrating AI into their day-to-day workflows for the past few years, the following five themes and specific questions are what business leaders need to start asking their teams to get to the real root of AI ROI:
- Revenue acceleration: What work are we able to deliver faster that unlocks more capacity and allows us to identify new opportunities that we otherwise might have missed?
- Quality improvements that reduce risk: What errors, issues, or exposures are caught earlier or avoided entirely?
- Strategic engagement: How does speed, responsiveness, or quality help corporate tax, legal, and risk and compliance functions move from perceived cost centers into demonstrable value drivers for their organizations?
- Talent retention: Does AI reduce burnout, improve job satisfaction, or increase leverage for top performers?
- Speed to value: How quickly do teams move from pilot to measurable outcomes—and what blocks adoption?
The New Benchmarks of Success
The answers to these questions will not only help business leaders get a more accurate sense of the role AI is currently playing in their organization, but they will also help establish benchmarks and best practices for what successful AI integration projects look like. If, for example, a corporate tax team asks the question: How is AI helping us reduce risk for our organization, the conversation that ensues will spark new ideas and inspire the art of the possible. Perhaps they will discuss new ways of modeling potential tariff scenarios on future earnings and tax liabilities, or faster methods of collecting the data they need to file quarterly reports that are now suddenly within reach.
For generations of business leaders weaned on the wisdom that you can’t manage what you can’t measure, the rapid growth of AI has raised more questions than answers. It’s time for the conventional units of measuring business success to be updated to reflect the sweeping impact AI is having across all facets of professional work.
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