Name: AIQ Insights: What the Data Reveals
Uploaded: 2026-10-02
Duration: 11 min 41 s

The Fortune AIQ 75 evaluates how the nation’s largest companies are putting AI to work, using a weighted set of measures that combines companies’ own assessments with feedback from technology leaders across their industries. As Senior Vice President of Global Operations & Transformation, Holly Briedis has seen the patterns behind the rankings up close: which industries are pulling ahead, where the biggest surprises are, and why so many well-resourced companies still aren’t translating investment into results. She’ll share what the data says about the state of enterprise AI in 2026 and what it predicts about who leads next. 


Holly Briedis, Senior Vice President, Global Operations and Transformation, ServiceNow 
Jeremy Khan, AI Editor, Fortune 

AIQ Insights: What the Data Reveals

Conferences

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fortuneaiweekly

OK, let's get started. So, what does the data from the Fortune AIQ 75 actually tell us? Please welcome to the stage ServiceNow's Director of Futures, Diana David. So Diana, well first of all, you have this really interesting title on LinkedIn. Uh, I, I just read one of your tongues, but on LinkedIn you call yourself a forward deployed futurist. Can you just very quickly tell us what, what that's really all about? What does that mean? I help people at the top of leadership at the top of companies see around corners, and I used to be just a futurist, uh, and the more. CEOs that I talked to, the more they keep saying we need 4 deployed employees, um, we need people to be out on the edge to bring us back the insights about what is actually happening in AI in our companies, and I thought, yeah, I wanna be a forward deployed futurist. So there you go, that's my story and I'm sticking to it. I'm gonna have to add forward deployed to to my title now. There you go. Exactly. I think I've always been forward deployed. Um, anyway, uh, looking at this is the 2nd year that we have done an AIQ list and, and service, it's the list is based in part on, on ServiceNow's AI maturity index which you've done for a number of years. And one of the interesting things that we, you saw last year, um, actually is that there was a kind of dip in preparedness by large companies, um, which is surprising because I was actually. Of, you know, several years into the generative AI boom, you'd think there was kind of going to be this trend of companies getting more and more mature and more ready, and you actually saw this dip last year, and now we've seen a rebound again this year. What is going on here? Why was there a dip last year and why maybe has it rebounded again this year? Yeah, that really surprised us too. In 2024 we started this and we thought it's just going to go up and up and up and everybody will be excited and Uh, the second year we saw a dip, 20%. It was not a small dip, and I think what happened based on customers that I speak to is really that the noise was out there. AI was everywhere, but it hadn't really filtered into company value, um, and of course you saw the headlines on that, um, and then now we are in a period where people aren't saying, am I gonna use AI? Am I not, but they are really. Starting to dig in and rethink work and so while 59% in this year's survey are beyond the AI pilot phase, only 9% are doing agentic autonomous multi-step workflows that are not checked by human beings at every step. So there are still lots to play for. I can't promise you that there won't be another dip next year, but it's just so insightful. To be tracking these pacesetters interesting and the pacesetters in the ServiceNow AI maturity index, that's as you say, it's only 9% of companies. A lot of them are the companies that are represented on the Fortune AIQ list. But what really sets them apart when you're looking at that 9%? What really Differentiates them from those that don't make that cut, so the pacesetters and in particular I'm talking about the AIQ 75 and this year what we saw this year was 36% of them are looking at. Really broadly scoped workflows, so not just one little point of sale. It's really autonomous multi-step workflows, and it's not just how many people are doing it, it's the gap that's versus 2% of people who are aspiring pacesetters who are not doing that. And then the other one was AI vision, so a clear, strong AI vision that was around 57% versus 21% data everyone's. Boga Bear, 64% of pacesetters were clear and aligned and on the path to more unified data versus 14%. But the biggest one, which we'll hear about in the later panel, was talent investment. That was the biggest gap. We had 57% of our pacesetters were investing in ongoing talent upskilling specific to their AI business reinvention versus. 4%. That was the biggest gap. It's really, it's operational discipline, right? It's not just technology, operational discipline and transformation. Yeah, and it's not just about technology. It's about making sure your workforce is ready to use that technology, feels comfortable with it, knows how to do it. That's fascinating. And there's a lot of complaints out there, you know, that companies are still not getting value from AI investment. They're not finding ROI. I think, you know, the AIQ 75 are actually the companies that have found value. And but I think what's less reported is how big that value can be. Oh my God, 160% ROI. Yeah, that's a big number. It's a big, I mean, it's worth, it's worth investigating that. Yeah. Where are we seeing industries that are sort of surging ahead in this, and are we seeing any that are falling behind? What sort of explains some of the industry differential we've seen? So it was really interesting to me. That was the biggest surprise in this AIQ 75, of course. Companies led that was something like 1 in 5, but then no surprise to us New Yorkers financial services that was the next step, um, but what was more of a surprise is that um we had construction and engineering had 6 spots we had food 5 spots, um, health care 5 spots. I think that what I love about that is of the 75 companies. We have 34 industries represented, which is amazing. So that says to me that it's not concentrated in one tiny little segment of the economy. It is everything everywhere all at once, and we had agribusiness and aerospace and telco and travel and semiconductors and steel. It is. There to play for for any company in any industry. Great, um, and I'm gonna come to the audience for questions in just one second. We'll see if we can sneak in a question. But before we do that, um, one of the differentiators seems to be, and I, I see this when I go out and talk to companies, a lot of the companies that are finding success are those that are actually investing in business transformation. They're actually redesigning processes. And I think there was particularly when AI agents became a thing maybe a year ago, a lot of people thought, oh this is great, I can just drop these agents into some existing workflow or I can just, you know, take some employee and my current employees and I'll just substitute one of them with an agent, but I guess that doesn't work. What are you finding when you talk to companies and you look at that? What, what are you seeing in terms of the process reengineering that differentiates success? So I think that um the engineers in uh in our company and in and in our inside of ourselves love the idea of just re-engineering the process but I think it starts with leadership. I think it starts with leadership growth mindset, an idea and a vision for change of what the company can become followed with. Specific training around um AI and specific functions and so companies that I talked to who really are thinking almost in a day zero mentality of what could this process be if I designed it today and you know not just how can I sprinkle AI on something probably. A very old or broken process to make it go even faster. That's just not solving the problem faster. Got it. Uh, questions. Anyone have questions from the audience, please raise your hand and we'll get to you. And if I don't see any, everyone's very shy this morning or afternoon. Uh, I'm gonna keep going then, uh, not seeing any questions from the audience. Um, you, you're talking about how. Companies try to re-engineer processes. Another thing I've heard some executives say is the technology is moving so fast they're afraid they're going to design a process for today's technology and then it'll be obsolete next year and they'll have to do all that work all over again. You're, you know, helping companies see around corners. How do you, how do you, how do you talk to them about that issue? How do you futureproof what you're doing today? Um, it's a great question, and I do hear that when I'm speaking to customers, but it's back to that. How can I have the vision, have, uh, you know, have the data aligned, and then from there start to. Decide which workflows I need to address, have ownership over the workflows, and iterate. It is, you know, a design process whereby we're taking our companies into the next era of business reinvention. And I don't think that any company is going to succeed by doing some kind of top down plan where you know one person or one strategy team is redesigning everything immediately. I do think that there is an iteration that we are starting to become more comfortable with. Interesting. And are there any tips for making that process flexible to have that ability to iterate? I think that scares a lot of executives. Well, I think about it from the perspective of, you know, a good foundation, your good data foundation, um, and then good visibility, and then the middle part is where we're starting to iterate. So we have AI control tower we're looking across the organization because one of the things that I'm really excited about is how. Um, different processes start to interact, uh, and you have to have transparency and you have to have some visibility as to how that's happening, um, so having the, the visibility from across the organization and a very strong foundation allows you to be flexible. Interesting. Um, another thing that a lot of companies did is initially they kind of gave everybody AI tools and they let sort of let 1000 flowers bloom and then they've said no, no, that's too expensive. We're not actually getting any productivity gain from that, uh, and they've had to now concentrate on some very specific use cases to scale up. Is there advice you provide in terms of how to find, find those, which, which are best? Um, that, that's sort of my pet peeve is AI adoption for everyone, and it, I get it because it's a great CEO story. 95% of everybody has X, Y, Z, but it is not translating into productivity and it's often not with training and um that doesn't equal maturity. So when we think about AIQ and the, you know, AI intelligent quotient. Is really about a mature um agentic um company that can think about what are our workflows uh in fact next year we're going to add uh AI and Agentic to the AIQ and it's about what are we deploying and where it's about how are we realizing actual commercial value. Um, and that is what I think true maturity for business is going to mean versus everybody has, you know, AI in their pocket, but they're not using it. Diane, thank you, Diane, thank you so much. Uh, we're out of time, but thank you very much. It was great insights to kick us off from the Q75. Thank you so much.