82% of Companies Are Seeing Positive AI ROI

**Nathaniel Whittemore** (0:00)
Today, we are doing a first readout of some of the results of our AI ROI Benchmarking study. And it turns out that AI is already, nascent though it may be, driving quite a bit of value. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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Now today, we are finally doing a first readout of the AI ROI benchmarking study. This is the thing that I asked you folks to contribute to back in November, and the reason it's taken a little longer than we thought to process it all is that you guys way over delivered for which I am incredibly appreciative. So what we're going to do is talk a little bit about how we set this up, what the composition of the respondents were, and then we're going to get into what we actually found out. First of all, let's talk about the set up. My big thesis heading into 2026 is that there's going to be much more emphasis on understanding the real impact of AI, rather than just doing things in the dark. Now, I do not believe that in short order, we're going to have any super common or very clear standards when it comes to AI ROI. I think a lot of people are going to experiment with a lot of things, and that's definitely the spirit of this. In no way are we contending that this is the only way to measure ROI. In fact, one of our key acknowledgments is that this is all self-reported. However, the way that we broke down different types of impact is that we put together eight impact or primary benefit categories that captured in our estimation, a pretty big chunk of the value that people were getting out of AI deployments and initiatives. That includes things like time savings, cost saving, increased output, improvement in quality, increased revenue, new capabilities, reduced risk, and improved decision making. Now, as you can tell, some of these have a quantification that goes with them. So for time savings, it was hours saved for a week. For cost savings, it was an estimation of cost reduction in percentage terms. Increased revenue, increased output, and improved decision making were all again estimates in percentage. Then new capabilities and risk reduction were both qualitative fields where people could describe what the new capabilities were or how risk had been reduced. We also used a numerical scoring system, a 1 through 5 scale where 1 is negative ROI, below breakeven, 2 is breakeven, 3 is modestly positive, 4 is significantly positive, and 5 is transformational. Now throughout this, you will sometimes hear me refer to high ROI, which is our shorthand for significant plus transformational, basically anything above modest. I do also want to point out, as this was a nuance that was lost in some reports this year, that negative ROI does not mean program failure. It can mean that, but at this stage, as early as we are, it more often means an AI initiative that hasn't paid back yet. And of course, there's no guarantee that it does, but when you dig into even the very small percentage of people that were sharing use cases with negative ROI, it tended to be about high setup costs and nascency of the programs rather than the AI just not working for its intended purpose. Now, as I mentioned, you guys really showed up. We had over 1200 unique respondents and over 5000 total use cases. And so where does that leave us in terms of the rigor of this study? By no stretch of the imagination is this some super scientific and highly controlled survey. We put it out to you guys as the listening audience, asked anyone who wanted to to show up and gave you the chance to self-report. We had, as you'll see, a pretty wide diversity of contributors across different industries, org sizes and roles. But there's certainly some concentrations. You're going to see a concentration in the technology industry as well as professional services. You're also going to see a concentration around small enterprises and solopreneurs. It's clearly a big chunk of this audience. And while some of those things impact the results, our argument is not that our results are a definitive look on what AI ROI looks like right now. Instead, what I believe is that the signal is so clear that as part of the emerging body of AI ROI exploration, this is a powerful signal that gives us a strong sense of the trajectory of where things are going. So let's talk a little bit more about the sample size. You can see we had heavy concentration among small organizations of 1 to 50 That represented about 44% of the total contributors. The rest were fairly evenly split. The next largest category was from organizations with 5,000 plus at around 18%. And then 51 to 200, 201 to 1000, 1000 to 5000 all had between about 11 and 14%. We had a similar diversity of role. Although again, that C-level founder at 35.1% reflects the heavy concentration of small organizations and solopreneurs. We also had 19% at director level, 15% at manager level, 14% who consider themselves an individual contributor, 8.5% at VP and 7.5% who said other. As I mentioned, technology and professional services dominated, with a lot of folks also coming from education, healthcare and manufacturing. So what did we learn? The big banner highlight for sure is that people are, right now, realizing value from AI, and they expect it to grow. 82% of companies reported positive ROI from AI, 37% reported high ROI, which again means significant or transformational. A full 96% anticipate positive ROI within 12 months. When you look across the use cases, about 45% reported modest ROI right now, compared to 28.1% who reported significant ROI, 8.8% who reported transformational, 12.5% who were at break even, and just 5.6% who were at negative. In the anticipated ROI, the big expectation was a shift from modest to significant, with almost exactly half anticipating significant increases in the next year. You can see that across organization size, the average ROI reported per use case was right around that modest level of 3 However, there is a subtle but clear pattern where the smaller the organization, the higher the reported ROI. Now, I think in some ways this makes intuitive sense, and I think it's about nimbleness having advantages. A lot of what AI is good at, saving time, increasing output, is especially relevant inside small organizations who are the most resource constrained. Now, those small organizations also project higher ROI in the future. Although again, on an organization level, every single organization size projects a move from the modest ROI level currently to a significant ROI level in the future. When you go category by category, and we're going to do a little bit of that in this readout, small companies tend to overperform on each particular quantification of impact category as well. For example, among use cases whose primary benefit was increasing revenue, respondents from the smallest organizations reported an average of nearly a 25% revenue increase, whereas all the use cases from all the other size organizations were between 10 and 15%, which by the way is still nothing to laugh at. You also see some interesting differences of perceived impact by role. As I mentioned before, we definitely think that there is a solopreneur effect, where the C levels and founders were seeing a much higher rate of significant and transformational ROI. In fact, among the C level and founders, over half of use cases were perceived as having high ROI right now. Interestingly though, this slant towards more senior roles reporting higher ROI does seem to hold a little bit more generally. For example, VPs reported 28% of their use cases having significant ROI, as opposed to 18.1% for directors and 19.8% for managers. My speculation on that is that the more senior you are, the more the use cases that you're involved in are big org-wide and systemic, and so have a better chance to have significant or transformational impact. But that's certainly something that we want to dig into more in future surveys. When you look at high ROI by industry, which again means the use cases that report significant and or transformational ROI, it ranges from a low end of energy reporting around 23.5% high ROI use cases, all the way up to nearly half with education reporting 47.1%.