The second edition of ServiceNow’s AI Maturity Index, with results disclosed during last week’s Knowledge25 conference, delivers strong insights into the mindset, organizational approaches, and priorities of those companies that earn AI “pacesetter” designation among the 4,500 organizations represented.
At the same time, one of the top-line findings may come as a bit of a surprise: enterprise AI maturity actually dropped 9 percentage points, from 44 to 35 (on a 100-point scale) year over year, a drop that ServiceNow execs put in context throughout the course of the week.
Saying the results highlight a foundational challenge for companies, ServiceNow’s President, Chief Product Officer, and Chief Operating Officer Amit Zavery said many companies are stuck with siloed data and AI agents, as well as disconnected legacy systems. “Despite the explosion of AI tools, many companies are still missing something crucial: orchestration,” Zavery said. “AI agents are popping up everywhere but not working together.”
Indeed, one telling finding is that 55% of those surveyed have rolled out 100 or more different AI use cases, reinforcing the point that AI agents are becoming omnipresent.
Dave Wright, chief innovation officer at ServiceNow, said a meeting with customer CIOs last week sheds some light on why “maturity” may be down: the pace of technology advances from AI to GenAI to agents, plus an explosion in potential use cases, may be giving the pause on how quickly to move ahead.
Channeling those CIOs, Wright said, “We know what to do with it and when you saw the scale of what you can do with it, now it’s actually like, are we sure what we want to do with it? Or could we do things in a different way?” CIOs, he said, are starting to recognize what they don’t understand.
The index measures organizational performance across five pillars of AI maturity: AI strategy and leadership, workflow integration, talent and workforce, AI governance, and realizing value in AI investment. Just 18.2% of respondents’ firms achieved “pacesetter” designation for those “elite” performers outpacing the rest of the group.
Innovation Mindset and Metrics
There’s a significant difference between pacesetters and the rest of the field in terms of working with an AI mindset. Among pacesetters, 53% have made significant progress in creating an AI innovation center, vs. 38% of the overall survey population.
Such innovation centers reflect a level of maturity that sets leaders apart, indicating “That level of maturity and understanding that you need to attack this holistically, that you can’t do it the way you did traditional IT where everyone built these systems of record in silos,” Wright said. “The people who are really moving ahead in AI will know this: this needs to go across all silos…to be centralized in how we think about deploying it.”
Innovative companies and those moving ahead aggressively with AI place high priority on selecting, retaining, and growing the best employees. Among pacesetters, 50% strongly agree they have the right mix of talent. Fully 80% — 4 of 5 — provide training and support to upskill employees, vs. just 54% of others.
In a finding that relates closely to the innovation mindset and the notion of a centralized innovation center, 63% of pacesetters have AI-specific policies addressing data governance and data security needs. Among those that don’t have pacesetter status, only 42% have similarly prioritized AI governance. Among pacesetters, 72% assess potential AI applications and understand data requirements as part of their governance initiatives. For others, it’s just 48%.
The delta when it comes to governance is telling. Data governance and AI governance “is actually holding people back. If you think about the speed at which AI is evolving, the speed at which the conversations about AI are increasing and accelerating, governance isn’t one of those conversations that are keeping up with all the cool tech,” said Brian Solis, head of global innovation at ServiceNow.
When it comes to measurement and metrics, there are a couple of key findings that reinforce the overall level of maturity: only 29% of companies strongly agree they have a defined set of metrics to measure return on AI transformation. But among the leaders, 49% strongly agree they have a defined set of metrics.
ROI Under the Microscope
Once a clear set of metrics are in place, it follows that companies will be better able to measure their performance and demonstrate real ROI — which of course is a top priority of the C-suite when it comes to AI investment.
Across respondents, 67% say AI has increased gross margin in their company by an average of 11%. For pacesetters, 83% of respondents say gross margin has increased, vs. 64% of others. Drilling deeper into ROI data, 56% have improved experiences, while 55% have increased efficiency and productivity through their agentic AI initiatives.
ServiceNow execs described the quickly evolving approach to metrics, financial impact of AI, and how people play into those factors. Solis said many CIOs are measured on their ability to realize an annual percentage of cost “takeout.” But an evolving view focuses on what they could do if they took out that cost but then reinvested the savings. “What if we create net new services or products or capabilities because of AI where human and machine work together to do what they couldn’t do yesterday?” Solis said. “Pacesetters are finding new ways to challenge their own conventions, to explore new possibilities with AI and that talent, those skills.”
Final note: Among pacesetters, 66% employ a tech platform approach vs. 46% of others. In this context, a platform refers to software that leverages a single codebase to manage an entire enterprise. This means they have eliminated, or are working to eliminate, silos to allow data to flow between business functions, resulting in a central repository of information from systems and AI tools.
In a tech platform approach, customers are driving toward centralized control and visibility spanning agents, applications, and platforms from a range of software suppliers, Wright said. In ServiceNow’s case, the company positions its platform as the solution to customers’ need to centralize data and centrally manage AI agents.
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