82% of Companies Are Seeing Positive AI ROI
The AI Daily Brief: Artificial Intelligence News and Analysis
Nathaniel Whittemore
4.7 • 763 Ratings
🗓️ 19 December 2025
⏱️ 23 minutes
🧾️ Download transcript
Summary
A first readout of the AI ROI Benchmarking Study shows that real business value from AI is no longer theoretical: 82 percent of organizations report positive ROI today, 37 percent report significant or transformational impact, and nearly all expect gains to accelerate over the next year. Drawing on more than 1,200 respondents and 5,000 use cases, this episode breaks down where ROI is actually coming from, why smaller organizations are often seeing outsized gains, how time savings compare to strategic benefits like new capabilities and decision quality, and what the data says about agents versus assisted AI at this stage of adoption.
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Transcript
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| 0:00.0 | Today we are doing a first readout of some of the results of our AI-R-OI benchmarking study. |
| 0:04.1 | And it turns out that AI is already nascent though it may be driving quite a bit of value. |
| 0:10.9 | The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. |
| 0:25.1 | All right, friends. |
| 0:26.7 | Quick announcements before we dive in. |
| 0:31.4 | First of all, thank you to today's sponsors, Super Intelligent, Robes and Pencils, Blitzy, and Rovo. |
| 0:37.4 | To get an ad-free version of the show, go to patreon.com slash AI Daily Brief, or you can subscribe on Apple Podcasts. And if you are interested in sponsoring the show, send us a note at sponsors at AIDailybrief.aI. Also, we're going to be talking about research today, and if that is something that is interesting to you, keep an eye on AIDB Intel.com. That is going to be the home and hub for a bunch of different initiatives around research, information, benchmarks that we have planned for the new year. I'm looking for people and companies to join an |
| 0:58.0 | AI tracking panel, and you can also sign up for future research updates. Again, that's at |
| 1:02.1 | AIDBIntel.com. Now, today we are finally doing a first readout of the AI-R-OI benchmarking |
| 1:09.4 | 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 setup. My big thesis heading into 2026 |
| 1:32.6 | is that there's going to be much more emphasis on understanding the real impact of AI rather than just |
| 1:37.8 | doing things in the dark. Now, I do not believe that in short order, we're going to have any sort of |
| 1:42.8 | 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 |
| 2:01.4 | put together eight impact or primary benefit categories that captured in our estimation a pretty |
| 2:07.0 | big chunk of the value that people were getting out of AI deployments and initiatives. That includes |
| 2:11.8 | things like time savings, cost saving, increased output, improvement in quality, increased revenue, new capabilities, |
| 2:19.7 | reduced risk, and improved decision making. Now, as you can tell, some of these have a quantification |
| 2:24.4 | that goes with them. So for time savings, it was hours saved for week. For cost savings, |
| 2:29.3 | it was an estimation of cost reduction in percentage terms, increased revenue, increased output, |
| 2:34.7 | and improved decision making were all again estimates and percentage, and then new capabilities and risk |
| 2:38.6 | reduction were both qualitative fields where people could describe what the new capabilities |
| 2:42.3 | were or how risk had been reduced. We also used a numerical scoring system, a 1-5 scale |
... |
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