# Two studies. One year apart. AI ROI remains flat

Two reports, one published a year back and one last month about AI ROI and something in there is really surprising.

MIT study (Jul 2025): only 5% of AI pilots in companies actually create real financial value.

McKinsey study (Aug 2026): only 6% of companies are what they call "AI high performers."

Two different teams. Two different ways of researching it. Different sample size. But almost the same number.

This is not a coincidence. This is telling us something real.

And here is the part that is worrisome. McKinsey in 2026 report found 37% of companies say AI touched their earnings "a little". That number is basically flat compared to one year before (McKinsey published same report in 2025).

Meanwhile companies invested a lot more money on AI in that same year and rolled it out to many more teams. So more money invested, more adoption, but the return line is staying almost the same.

80% of employees still say AI makes them personally more productive. Only 37% of companies can point to real impact on earnings ("a little"). Everyone feels faster. Companies feel happier about imaginary ROI. But the P&L is not catching up, and it has not caught up in a full year, staying around mid-single digit (5-6%).

What is separating the small group who succeed from everyone else?

*   Buy the tool, don't try to build everything yourself. Companies working with outside partners succeed two times more than the ones building in-house.
    
*   Change how you work, not just add AI on top of the old process. The companies doing well are three times more likely to redesign their workflow completely.
    
*   Put money in the places like operations and back-office, not only sales and marketing demos. This is where the real ROI is hiding.
    
*   Leaders need to be personally involved. Not just leave it to the IT team, AI engineers or the data scientists.
    
*   The tool needs memory. If it forgets everything each time, people will stop using it, quietly.
    

So as always, technology (AI in this case) is not really the problem here. Maybe it is us, and how we are using/adopting/leading/implementing it.

References MIT study: [https://webberwentzel.com/News/Documents/2025/MIT1757411281972.pdf](https://webberwentzel.com/News/Documents/2025/MIT1757411281972.pdf)

McKinsey study: [https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/](https://www.mckinsey.com/capabilities/quantumblack/our-insights/the-state-of-ai#/)