Having spent 25 years analyzing enterprise IT — almost 13 of them at Gartner, known for its “Gartner Hype Cycle” that describes the rise and fall of emerging technologies through five distinct phases, from early buzz to mainstream adoption Michael Warrilow understands why some CIOs are skeptical of artificial intelligence.
But AI is different from other technologies, insists Warrilow, now founder and chief researcher at Virtified, a Sydney-based analyst firm that helps IT professionals adopt and refine emerging technology best practices.
In an interview with The Forecast at .NEXT 2026, Warrilow argued that AI is a profound computing disruption that demands hands-on experimentation, careful infrastructure choices, and a clear line between innovation on the one hand and the core systems that keep businesses running on the other.
If those conditions are met, he said, AI won’t follow the same predictable path traveled by other technologies before it. Rather, it will forge its own transformational future, for which IT leaders must start preparing now.
Is AI Hype?
In his conversation with The Forecast, Warrilow related his first encounter with AI. It was in the 1990s, while he was studying at Australia’s Macquarie University, but it never became his specialty. Like most people, it’s only in the last few years that he’s started interacting with AI routinely.
Warrilow’s gap in AI experience mirrors that of many senior IT leaders today. He knows what it’s like to look at AI from a distance and wonder whether it’s simply one more inflated trend. While still at Gartner, he joked that AI was too profound for him to cover. However, he later went back to the books to understand it better.
So began his journey to becoming an AI practitioner.
After learning more about AI, Warrilow began actively experimenting with it. For that reason, he said, his view of AI is built not on conference slogans but on direct use at scale.
“I’ve run over 180,000 prompts across multiple different AI providers and models to automate some research I’m doing,” said Warrilow, who encourages others to experiment in the same way to avoid becoming jaded about emerging technologies.
Although “there’s certainly a lot of AI washing that’s going on,” Warrilow acknowledged, he said dismissing AI because of a perceived AI hype cycle would be a dangerous mistake.
More Than Another Transformation Trend
The current wave of generative AI is only the opening chapter, suggested Warrilow, who said the technology already is useful for people who are not elite programmers — including himself.
“I've created industrial-scale code for my research purposes just by having meta prompting,” he said.
But large organizations are less enthused, acknowledged Warrilow, who conceded that many have spent hundreds of millions of dollars implementing AI without seeing meaningful benefits. It’s therefore not surprising that many CIOs are wary: They’ve seen expensive transformation programs before, and many have been conditioned to expect disappointment.
“Agile, digital transformation projects are one example that has caused the cynicism that exists around AI,” Warrilow said.
However, that doesn’t mean IT leaders should dismiss AI as another trend that will come and go, Warrilow stressed.
“This is the most profound disruption in my lifetime in computing,” he continued. “They need to get onto it.”
Leading Through AI’s Infrastructure Uncertainty
At Virtified, Warrilow is currently engrossed in virtualization and infrastructure research that’s helping enterprise IT buyers navigate a “once-in-a-decade disruption” and make more informed decisions.
He said a major shift for organizations is that they can no longer rely on a single vendor. Instead, they must rescan the field and understand where suppliers are strongest, noted Warrilow, who emphasizes fit, variation and what he calls “horses for courses.”
Nutanix’s “bottom up” approach aligns with that advice, he said. The company has focused on its strengths while adding compute, containers, Kubernetes and now AI, which is in contrast with attempts to force a simplified cloud operating model into enterprise environments that are inherently more complex and heterogeneous.
That complexity has been compounded by the sudden and overwhelming AI opportunity, which Warrilow said requires an analogy to help ordinary users and executives make sense of it. “AI is nothing but the new Excel,” he proposed. “Excel is the world’s most common integration tool and a popular method for helping make business decisions.”
It’s not that AI is trivial, he said. It’s that people need relatable mental models to help them adopt it intelligently.
And yet, the real challenge for executives isn’t AI at all. It’s leading under conditions of profound uncertainty, Warrilow argued. Although cynicism once was a useful defense against hype, it can now become a career- and institution-limiting reflex, he pointed out, stressing that business leaders who are tempted to withdraw from AI should instead see it as a call to learn, test, translate and keep moving.
AI Demands Both Urgency and Restraint
Although business leaders shouldn’t dismiss AI, neither should they deploy it recklessly, Warrilow cautioned, recommending that they distinguish between systems of record and systems of innovation.
“Systems of record [are] things that keep the lights on,” he said. “Don’t put AI near that.”
Because generative AI is non-deterministic, the same prompt may not yield the same answer every time.
“You don’t put that near your banking system,” continued Warrilow, who said AI is better suited to support and innovation use cases. “That’s where we fail fast [and] spend a bit of money.”
CIOs looking to budget for AI experimentation should combine it with “something boring” to modernize legacy technology, Warrilow added. “You are more likely to get the funding if you put the AI label on top of it,” he said.
From an IT infrastructure perspective, preparing for edge and data center inferencing is a key way to realize the value of investing in a modern ‘stack’. Warrilow’s discussions with leaders of IT infrastructure have shown him that value realization is critical. Successful infrastructure teams can articulate measurable business benefits linked to the original business case.
It’s not just business and IT leaders who must embrace the changes that AI is bringing, Warrilow noted. It’s everyone, because AI is an inflection point that will fundamentally alter how work, decision-making and competition operate.
“All of society needs to prepare, because it’s coming for all of us, whether you’re a teacher, an actor, whether you’re an artist, whether you’re a musician, whether you’re a professional,” Warrilow concluded. “It’s just starting.”
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Gary Hilson has more than 20 years of experience writing about B2B enterprise technology and the issues affecting IT decisions makers. His work has appeared in many industry publications, including EE Times, Fierce Electronics, Embedded.com, Network Computing, EBN Online, Computing Canada, Channel Daily News and Course Compare.
Ken Kaplan contributed to this story. He is Editor in Chief for The Forecast by Nutanix. Find him on X @kenekaplan and LinkedIn.
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