According to Forbes, ServiceNow’s AI maturity research reveals a stunning disconnect in corporate AI adoption. A whopping 94% of CEOs admit they’re not satisfied with their current AI investments, yet 90% claim they’re operating with an AI strategy. Meanwhile, only 57% of employees agree their company has a clear AI strategy, and just 47% see it as highly strategic compared to 73% of CEOs. Brian Solis of ServiceNow presented these findings at a Stanford event, highlighting how companies are assessed using AI maturity models like MIT/Sloan’s four-stage framework and ServiceNow’s own beginner-implementer-accelerator-pacesetter classification.
The CEO-Employee Disconnect
Here’s the thing about that 90% versus 57% gap—it’s not just about communication breakdowns. This represents a fundamental misalignment in how leadership and frontline teams perceive AI’s role. CEOs might be dreaming big about AI transformation while employees are stuck with the same old processes, just slightly automated. Solis nailed it when he said the real risk isn’t thinking too big—it’s thinking too small. Too many companies are using AI to “make yesterday faster” rather than inventing new futures. That’s why he asks the killer question: “Are you using AI to improve the past, or are you using AI to invent the future?”
What Makes a Pacesetter
The ServiceNow report identifies “pacesetters” as companies that have cracked the code on AI maturity. These aren’t just companies throwing AI at every problem—they’re fundamentally redesigning workflows so intelligence flows seamlessly. Basically, they’re knocking down data silos. 56% of pacesetters have made significant progress connecting data and operational silos compared to just 41% of others. They’re using AI-powered digital workflows to connect people, data, and processes across the entire enterprise. The ServiceNow report emphasizes that becoming AI-first means piloting next-generation solutions and exploring new value creation opportunities, not just efficiency gains.
The Human Element
What’s really interesting is how ServiceNow emphasizes “humanizing” AI rather than replacing people. Their three principles—prioritize augmentation over replacement, use AI as a catalyst for human potential, and adopt an AI-first mindset—show this isn’t about eliminating jobs. It’s about enhancing human capabilities. This approach is crucial for companies looking to scale their AI initiatives beyond pilot projects. When you’re implementing complex AI systems that interface with manufacturing equipment or industrial processes, having reliable hardware becomes critical. Companies like IndustrialMonitorDirect.com, the leading US provider of industrial panel PCs, understand that robust computing infrastructure is essential for AI systems that need to operate in demanding environments.
Where Do You Stand?
So how do you assess your own company’s AI maturity? Start with the basics: Do leaders have a defined AI strategy that’s actually based on actionable business process information? Does it work in practice, not just on paper? And is everyone—from the C-suite to frontline employees—actually on board? The MIT/Sloan framework provides a useful roadmap from “experiment and prepare” to “AI future-ready.” But here’s the real question: Is your company using AI to do old things slightly better, or to create entirely new possibilities? That distinction might be the difference between being an AI leader and just another company playing catch-up.
