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As any CIO will tell you, the pace of technological change has been on the upswing for years.
The result has been a slew of new and transformative technologies quickly coming to the market and near constant improvements to existing tech.
With artificial intelligence and robotics becoming mainstream at a break-neck pace and quantum computing nearing commercial use, it’s easy to get excited by all the advancements.
But CIOs say many technologies aren’t delivering the expected benefits — at least not yet. It’s a typical trend, where a technology’s expectations exceed what it can actually do at the moment. Gartner’s Hype Cycle calls this stage the “peak of inflated expectations” — which happens just before disillusionment sets in.
CIOs are typically on the front lines of all this. They’re either caught up in the excitement or having to manage expectations when hoped-for plans exceed reality.
“It is important to adopt a realistic perspective of the capabilities of the technology balanced against the nuances,” Campbell says.
A lot of factors contribute to inflated expectations. Some technologies hit overhyped status when their actual capabilities fall behind what users want them to do. Others hit that point when they take far too much time, effort, and money to work to their full potential.
We asked IT leaders their thoughts on what’s overhyped today and here’s what they had to say.
1. Generative AI
CIOs once again cite generative AI as an overhyped technology, making it the third year in a row that gen AI has landed on this list.
Sources are in near unanimous agreement that the hopes for generative AI outpace what it’s actually capable of doing — and doing well — at this point.
Campbell points to the challenges of using gen AI in her field as case in point, noting that “the specific concern around a wide scale replacement of lawyers with gen AI technologies is overhyped today given where the technical capabilities currently stand.”
“There is significant potential value for gen AI in firm operations and augmented services related to the practices of law,” she says. “There are opportunities to enhance productivity, to improve operational processes and processes related to legal practices, and to elevate client outcomes and experiences. There are further opportunities to explore new revenue paths, and opportunities for cost reductions related to operations through automation. However, the current state of gen AI technology as used in the practice of law still faces some challenges. Questions remain around the accuracy of outputs and related time investments of legal and business professionals to vet and balance the outputs against their expertise.”
With nearly nine in 10 gen AI pilots failing to reach production, according to research firm IDC, it’s little wonder CIOs are increasingly resetting their gen AI strategies for practical solutions over experimentation. Still, lack of success metrics continues to haunt outcomes, and the state of what the technology can presently do is beginning to sober expectations.
2. Agentic AI
Others say agentic AI is overhyped, too, and cite many of the same reasons Campbell gives for putting gen AI on this list.
Dhaval Moogimane, leader of the high-tech and software practice at West Monroe, a digital services firm, says this of agentic AI: “I think agentic AI is transformative, but it’s going to take longer than people think to have agents work with other agents. We’re going to see a lot of innovation by tech companies and software providers, but the world that is envisioned of agents working with other agents without human intervention is further off than predicted.”
He’s not the only one thinking this way.
Research firm Gartner in June 2025 predicted that more than 40% of agentic AI projects will be canceled by the end of 2027, “due to escalating costs, unclear business value or inadequate risk controls.”
“Most agentic AI projects right now are early-stage experiments or proof of concepts that are mostly driven by hype and are often misapplied,” Gartner senior director analyst Anushree Verma says in a news release about the firm’s prediction. “This can blind organizations to the real cost and complexity of deploying AI agents at scale, stalling projects from moving into production. They need to cut through the hype to make careful, strategic decisions about where and how they apply this emerging technology.”
Moreover, Gartner in that same release says, “many vendors are contributing to the hype by engaging in ‘agent washing’ — the rebranding of existing products, such as AI assistants, robotic process automation (RPA) and chatbots, without substantial agentic capabilities” and “estimates only about 130 of the thousands of agentic AI vendors are real.”
What isn’t helping is the lack of a standard definition of what constitutes an AI agent. CIOs will need to learn how AI agents and agentic AI differ from each other, as well as how to determine whether a business process is a strong candidate for agentic AI in order to make good on early promising use cases.
3. Digital employees
On a related note, Yugal Joshi, a partner at research and consulting firm Everest Group, considers digital employees as an overhyped tech.
“We are taking a massive leap of faith calling simple agents, which are LLM-wrapped chatbots or workflow agents, as digital employees. Though the concept has merit and is revolutionary, we are far from getting a true digital employee. In a similar way, general-purpose agents have been hyped up as well. These are supposed to do multiple types of tasks with agency and autonomy. But currently we have task-specific agents, and it appears that the industry is now moving in that direction. General-purpose agents will be multi-orchestrators than stand-alone agents by themselves.”
So, while Microsoft recently predicted that digital employees in the form of AI agents will soon upend organization charts, heralding the new role of “agent boss” to oversee teams consisting of people and digital AI employees, that future is likely farther off than touted.
4. AIOps and observability
This is another AI entry making its debut on the list this year. AIOps is an emerging discipline in which AI systems not only help identify issues with operations infrastructure but react to events intelligently to mitigate them.
“The promise of AIOps combined with observability running self-mitigated operations through better data linkages and insights has not materialized,” Joshi says. “The overload of noise from these tools combined with irrelevant telemetry has been a big bottleneck. There has been a significant time spent on triaging and understanding, rather than responding to businesses. As AI agents explode, these platforms will cover agent’s observability as well, that can make things even more challenging.”
5. AI in general
Some list AI in general as an overhyped tech.
As is the case with gen AI, tech leaders believe AI in general deserves this designation because expectations are outpacing reality at this point.
“There is so much misinformation and misunderstood information out there that AI has ended up on my list of overhyped tech,” says Drew DeNardo, who as CTO oversees IT operations at virtual care company JOGO Health. “Yes, it is a very transformative tech, but people think it’s going to magically solve all their problems. They think they can slap AI into the ecosystem and all the company’s problems will be solved.”
Tech leaders know the reality is much different, he says. “You need to be thoughtful and deliberate, and the companies that use AI to augment and to supplement their teams, who use AI to empower their teams and to make them more productive, are the ones who will be successful, where those who think they can use AI to cut people, the companies that have tried that approach, are failing spectacularly.”
Still, AI is beginning to reshape the job landscape, with company boards increasingly pushing CEOs to cut workforces in favor of AI.
6. Quantum computing
Yes, IT leaders recognize the potential of quantum computing, which uses quantum mechanics principles to perform calculations and as a result is exponentially faster and more powerful than the current class of computers.
But they also say quantum computing is still farther off in the future than the hype suggests, landing it on this list yet again this year.
“We’ve made some big leaps, but we’re not going to be significantly impacted by quantum computing soon,” says Brendan Arbuckle, CIO of The Jackson Laboratories.
That said, Arbuckle — like other tech leaders — does see quantum breakthroughs on the horizon and believes CIOs need to be planning for a post-quantum world, especially around encryption. But he doesn’t see the need for concrete plans for putting quantum computing itself to use for enterprise workflows in the upcoming few years.
7. Metaverse, AR/VR/XR and spatial computing
This is another category of tech making a repeat appearance on the annual list of overhyped tech.
Analysts and IT leaders agree that expectations on spatial computing — whether augmented reality, virtual reality, extended reality, or the metaverse — still outpace its value despite advances that have been made in the past several years.
“The metaverse, spatial tech, AR/VR — none of that really took off,” West Monroe’s Moogimane says.
He isn’t writing off the value of these technologies completely, though: As is the case with the other technologies now seen as overhyped, spatial computing has loads of potential; it will just require a lot of time and investment to reap the benefits it could produce.
“Any kind of major technology change that requires a change in how work gets done, that requires different forms of engagement and different workflows, takes longer for people to adopt,” Moogimane says. “So I think the expectations for this technology are right, but it will take longer than expected to get there.”
Everest Group’s Joshi has a similar take and cites specifically the industrial metaverse as being overhyped.
“The promise has been higher than the actual implementations,” he says.
There are definite use cases, Joshi believes, such as for design and maintenance of shop floors, with digital twins of high-end devices, and training. However, challenges around infrastructure costs, people training, interoperability, and poor UX has marred its adoption.
8. Multicloud
Many CIOs embrace multicloud but Joshi says few are getting all the benefits that this cloud strategy has promised.
“The [enterprise] objective to have uniformly synched interoperable workloads for multiclouds that allow them to address vendor lock-in has not worked,” he says. “Most enterprises are multicloud, but their bet on cloud vendors rarely change. They do not necessarily interoperate their workloads across different cloud platforms either.”
So while CIOs are more intentionally pursuing multicloud strategies, whereas previously many had found themselves there as a matter of near happenstance, interoperability and other key issues are adding complexity to the calculus.
9. Electric vehicles
Granted, this is not a technology that CIOs usually deal with, but some CIOs still put it on their list of overhyped tech.
Chris Grebisz, CIO of technology company Welocalize, is one of them. He described having to figure out how to put his Tesla into neutral when he took it to a car wash for the first time, saying that such routine actions have to be relearned with EVs.
And as he’s doing that, he’s finding that the user interface isn’t as intuitive as promoted.
“It’s going from 30 years of driving a car to something like an iPad, and I’m a tech guy,” he says. “Everything needs to be figured out. I have to go and read the manual.”
Grebisz says he now considers his Tesla a “transportation appliance” rather than a car, a mindset shift that helps him with the change management required when shifting from a conventional car to an EV.
He notes that it was a dramatic change, suggesting that true digital natives might find the shift easier to make.
The experience has also given him insight into how workers feel when a technology disrupts longstanding workflows.
“I was just really surprised by my experience. I thought it was going to be a lot easier,” he adds.
10. Green energy
David Williamson, CIO of Abzena, a life sciences company, goes even further and puts green energy in the overhyped tech category.
To be clear: He’s not against it. In fact, he, too, has a Tesla and has solar energy for his home.
It’s those personal experiences that led him to conclude green energy isn’t the silver bullet that some promise. To start, he — like Grebisz — found there’s a learning curve to driving his EV.
“My biggest complaint is they change the user interface all the time,” he says, offering that he has “watched a lot of videos to know what to do with the car.”
He has also found that both hot and cold weather wear down the battery, “so you think you have a certain range but you don’t.”
He has had a similar experience with solar panels, saying “the promise and the reality are different.
They get dirty and then lose efficiency, so they have to be cleaned. And the difference in their summertime and wintertime performance is significant.
And then there’s the surprise costs, with Williamson noting that he had to pay to connect to the grid and still gets charged a delivery fee.
Williamson says these experiences remind him that “we underestimate the impact of technology on the individual” and that “there’s gotchas with the technologies that aren’t discussed.”
Ren Ecosystem