A takeaway from the Gaming & Leisure CIO Roundtable

I saw a slide at the Gaming & Leisure CIO Roundtable that made me pause. More than 80% of surveyed gaming companies use generative AI. Only one in five reports meaningful ROI.[1]

With so much attention on AI, that gap deserves more conversation.

The research, from UNLV’s International Gaming Institute in collaboration with KPMG, also found that one in four companies has no structured way to evaluate AI ROI.[1]

Some initiatives are still early, and returns take time. But if we have not agreed on how to measure success, how will we know whether the investment is working?

What actually changed

It is easy to get excited about a demo. A report that took hours now takes minutes. Hundreds of guest comments become a clear summary. Those are useful capabilities. The next question is what they helped us accomplish.

Did the team use the time saved to follow up with more guests? Did we address a service issue sooner? Did we reduce repeat complaints? And did those improvements justify what we spent?

For me, that is where the conversation gets interesting. We should be able to explain what changed because of the investment, with something more concrete than “the team likes the tool.”

Are we spending money on the right problem

Imagine a player starts visiting less often. Their activity drops, and the system recommends an offer to bring them back. Seems reasonable. Except their last visit included a frustrating interaction at the Player’s Club that no one followed up on.

A bigger offer may get their attention. It may also leave the original problem untouched. If we could see their feedback alongside their visit history and gaming value, we might start with a phone call and a service correction. Then we could test whether that approach made a difference.

That is why I see guest feedback as an important part of this conversation. Gaming data shows activity. Guest feedback can help us understand what happened during the visit. Together, they give the team a better starting point for deciding what to do—and where to spend.

Agree on success before you start

Before a pilot, I would want the team to agree on the problem we are solving, who owns the response and what we expect to improve. Start with the current performance so there is something to compare against later.

Be specific about the return, too. Faster follow-up is worth tracking. Connecting it to a financial result takes more work.

Hours saved do not always mean payroll savings. And a guest returning after an offer does not tell us they would have stayed away without it. Where practical, compare similar groups or roll out the change in stages. Look at the additional contribution after relevant costs, and account for promotions, seasonality and other changes happening at the property.

Include the full cost as well: software, integration, training and the team’s time to manage it. That gives us a much more credible business case.

Who is doing something with the insight

AI could tell us that guests keep complaining about a long wait. If the same complaint is still showing up three months later, what have we gained?

Someone needs to review the findings, understand the cause and make a change. Then we need to go back and see whether it helped. That follow-through is easy to overlook when the conversation is focused on the technology.

Technology, operations, marketing and finance all have a role. The people using the insight should be involved from the beginning, with clear rules for guest data, human review and player protection.

My takeaway from that slide is that we should spend more time on what happens after the demo. Better information is valuable when it helps someone make a better decision and act on it.

For your next AI initiative, what result would make you say, “This was worth the investment”—and how will you know it happened?

Source

[1] UNLV International Gaming Institute and KPMG, The State of AI in Gaming 2026. Figures refer to surveyed gambling companies, not a census of casino operators. Research summary and full report