AI changes the ROI equation. Here’s how some have found success

Like many companies, Alight Solutions, a benefits administrator, has been searching for ways AI could improve operations and its bottom line.

While not a new technology to the company, Alight began assessing a different kind of AI tool in 2025. In September of that year, Alight became a beta user of a fraud detection recruiting agent from Phenom, an HR technology vendor. The company wanted to see if the agent could help identify fraudulent candidates early in the recruitment stage.

It didn’t have to wait long for results. During the testing process, the agent identified a candidate who applied for an open position twice, using a different name and email address each time.

“Even by catching that one person that we ultimately didn't hire, that was enough for us to say, ‘It's going to work for us,’” said Julie Eagy, talent acquisition operations manager at Alight.

While the agent showed where it might help save the company money, especially if it could prevent it from paying for an unnecessary background check, the greater value is time savings, Eagy said.

Alight provides an example of how measuring a return on AI investments can get messy. For many companies, the return on investing in AI tools might not be monetary gains but rather productivity gains or the ability for the AI agent to provide a missing piece within their organization.

That lack of clarity has led some enterprises to let go of some initiatives. A Pizza Hut franchisee, for example, sued the franchise in May claiming that an AI delivery management platform was counterintuitive in that it cost it millions of dollars rather than providing it with any kind of savings.

Despite AI’s mixed results, enterprises have continued to push forward with the technology, often leaning on productivity as a metric. Meanwhile, some small businesses, including SMBs, have been able to track monetary gains and returns from their AI projects.

A complicated situation

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