The 10 most overhyped technologies in IT

Today’s technology is the stuff of yesterday’s science fiction, with artificial intelligence, robotics, and spatial computing becoming mainstream after decades of, first, speculation and, then, development.

But are they all delivering as hoped? In some ways, yes; in a lot of ways, no.

It’s a typical trend, where expectations about a particular tech exceeds 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, whether because they’re caught up in the excitement or they’re having to manage expectations when plans exceed reality.

“We are realists in some ways, because we recognize there are limits to all this stuff,” says Daniel Uzupis, CIO and information security officer at Union Community Care. “We have to see past all the hype to see what value does a technology actually bring.”

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.

What technologies now fall into that overhyped category? We asked 10 IT leaders their thoughts on what’s overhyped today, and here’s what they had to say.

1. Generative AI

Generative AI tops the list of overhyped technologies for the second year, with near unanimous agreement that the hopes for genAI outpace what it’s actually capable of doing — and doing well — at this point.

“There is so much hype pertaining to [generative AI] today that some senior leaders are believing that it can be broadly applied without fully understanding this powerful technology and, more importantly, how it can be utilized in their organizations,” says Greg Barrett, who through GMB Consulting provides fractional and interim CIO and CTO services as well as senior advisory support.

Others have a similar take, saying people are too quick to deploy genAI without determining whether the tech will deliver returns.

“You still need to have a clear business case and understand what it is you’re trying to solve, for it to be worth pursuing,” says Atlas Systems CISO Kaarthick Subramanian.

That remains a challenge for many. As research firm Gartner finds, “Investment in AI has reached a new high with a focus on generative AI, which, in most cases, has yet to deliver its anticipated business value.”

2. Artificial general intelligence

It’s not just the generative version of AI that seems to be overhyped.

Peter J. Scavuzzo lists artificial general intelligence (AGI) as another tech garnering more excitement than it should at the moment, saying he wonders whether imaginations on what AGI can do (at least in the short term) have outpaced reality.

IBM describes AGI as “the science-fiction version of artificial intelligence, where artificial machine intelligence achieves human-level learning, perception and cognitive flexibility” and says that, while still theoretical, it “may be poised to revolutionize nearly every aspect of human life and work.”

Scavuzzo is holding back on his enthusiasm for now. “AGI is where AI has the cognitive abilities of humans, where it gets close to how humans operate, and I think we’re far off from that being possible,” says Scavuzzo, a partner and chief information and digital officer of accounting and advisory firm Marcum LLP as well as CEO of Marcum Technology.

3. AI in general

Sources agree that all the various types of artificial intelligence — from machine learning to natural language processing to large language models — hold incredible potential and already are delivering revolutionary returns.

But they note that AI is delivering solid returns in only a fraction of deployments, adding that many organizations have work to do before they experience significant (and not only incremental) benefits.

“I do think AI in many forms is overhyped and there are a lot of unrealistic expectations,” says Robert Field, CIO at Ozmosys and an advisory board member at FenixPyre, a cybersecurity company. “There’s a lot of promise in it and a lot of opportunity. But the reality of implementing AI is a lot more complex and a lot less glamorous than people talk about right now. Yes, we have to embrace it, but I also find that I have to level-set a lot of expectations.”

4. AI PCs

Similarly, Brian Jackson, research director for Info-Tech Research Group’s CIO practice, adds AI PCs to today’s list of overhyped technologies.

“This is such a clear-cut case of vendors trying to push something that they think is a differentiator to try to get people to buy new hardware,” he says.

They have reason to do so, Jackson explains. Many CIOs have lengthened their PC refresh cycles, replacing computers every four or five years now instead of every three years as had been the long-used timetable.

“This is a testament to computers being really good now,” Jackson says.

AI PCs have CPUs, GPUs, and NPUs selected to efficiently handle AI models locally; they’re billed as being faster and more powerful so they can deliver better performance both in computing and battery life.

Jackson says such capabilities will be needed in the future, but notes “we’re at least three years out” from that. Until then, he believes that the PCs in use today are fine for how most people currently consume AI — which is through cloud-based applications and not locally on devices.

“[Existing computers] have sufficient processing power, memory, and storage that we can use them for years,” he adds.

5. Next-gen anything and everything

On a similar note, Union Community Care’s Uzupis puts anything and everything labeled “next-gen” on the list of overhyped tech.

“What does ‘next-gen’ even mean?” he asks.

He says some vendors slap “next-gen” on their products too often and too freely, while others rush to get those novel capabilities into their products before they’re ready for prime time, earning that “next-gen” tag while leaving users to contend with buggy technology. “Or they’ve enabled AI features that no one wanted, and then you have to opt out of them,” he adds.

Uzupis counters all the overhype around “next-gen” products by using tried-and-true evaluation techniques — looking under the hood, so to speak, to determine whether the new-and-improved version really offers anything better and whether the cost of upgrading is worth the value it will produce.

“It really comes down to, ‘Does this product deliver?’” Uzupis says.

6. Quantum computing

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 that quantum computing is far in the future, tempering today’s excitement and hype about it.

“It’s still at a theoretical level. It’s going to take a lot to make it commercial, and it’s going to need a lot more research to get it going,” says Andy Thurai, vice president and principal analyst with Constellation Research, adding that the costs and resources required to develop and eventually run quantum computing only adds to the challenges of making it a reality.

“There are so many limitations to building a world-class quantum system that it is still a very scientific experiment in my mind,” he says.

7. Fusion power

On a related note, some also put fusion power in the overhyped category, seeing it — like quantum computing — farther from reality that its proponents make it seem.

Interest in fusion power isn’t new. But it got a boost with AI, which researchers say could help them finally deliver fusion energy (which in turn will help power energy-hungry AI systems).

Fusion also got a bump in collective attention when OpenAI CEO Sam Altman got into the field, backing Helion Energy and its plans to build the world’s first fusion power plant.

But don’t hold your breath, says Scavuzzo.

“This is going to help drive the next technology boom, but it’s not going to be something we see soon,” he says.

8. Avatars

AI is fueling another area that Info-Tech Research Group’s Jackson sees as overhyped, which is the notion of digital humans and avatars.

Jackson says the technology to create and use avatars is mature and does quite a good job at delivering digital humans who seem real.

In fact, digital humans are already in use today, in legitimate and problematic use cases as well as ones in-between, with varying degrees of human acceptance, he says. Many people will tolerate a customer service chatbot. They’re less tolerant of digital humans used in entertainment “unless there’s a clear artistic reason for them.” And most agree that deepfakes represent a big area of concern.

“But the way companies are thinking about this capability and the use of them [for interactions with real humans] gets a little bit far-fetched,” Jackson adds. “People say they’re going to create digital twins of themselves and send it to a meeting when they can’t make it. Unless it’s your CEO saying you’re going to interact with that avatar, people are going to drop out of [such] interactions. It’s just unacceptable.”

He adds: “I’m not saying never use this. There is tremendous value. But I think we’re going to take it too far, too quickly.”

9. Metaverse and spatial computing

Although the hype has died down on this class of technology in recent years, some say the expectations on spatial computing (whether augmented reality, virtual reality, extended reality, or the metaverse) still outpace its value — making it a worthwhile entry onto the 2024 list of overhyped technologies.

“The metaverse and AR/VR are technologies similar to blockchain where there was a lot of buzz initially, but it has quickly faded and been displaced by AI,” says Thomas Phelps IV, CIO of Laserfiche and a SIM Research Institute advisory board member. “In 2022 the metaverse took center stage at one of the largest technology conferences hosted by a leading analyst research firm. Last year, Apple made a big splash with Vision Pro. But after the initial coolness factor wears off, it’s hard to justify significant investments in the technology as most organizations have yet to realize sustainable benefits. It’s not easy to break out of niche applications to appeal to a broader enterprise market.”

He notes that “some devices are still clumsy to operate and uncomfortable to use for long periods,” which is further slowing adoption.

Others also label the metaverse/spatial computing overhyped, saying that although it has some worthwhile use cases, the cost of equipment (for consumers particularly) and the limited content has kept it from really taking off.

Tej Patel, CIO and vice president of IT at Stevens Institute of Technology, for example, says many enthusiasts had talked up the potential of spatial computing in education but have found that the benefits “do not justify the cost and efforts involved.” Stevens has an XR lab, but Patel says educators and administrators are strategic in its use, identifying learning experiences that deliver value that exceeds the resources required to run the lab.

10. Humanoid robots

This is another AI-related tech that some say has generated more buzz than substance at this point.

Make no mistake, humanoid robots are on the horizon and already are used to do some work, Jackson says. But they’re good at doing tasks, not entire jobs. The idea that “these humanoid robots are going to replace human workers who are agile at doing different tasks” remains an aspiration, not a reality.

“We’re at the very beginning; no one is relying on these to do real independent work,” Jackson says.

Rama Donepudi, vice president and CIO for global nutrition at Reckitt, has a similar take, saying the interest in humanoid robots is just approaching the hype phase. Like Jackson, Donepudi thinks the technology is a long way from being autonomous.

“We’re thinking it’s going to be like in the movies, but we’re not there yet. We don’t have fully automated lawn mowers yet, and robotic vacuums still get stuck under the couch,” he says.

And he expects when the first ones are deployed, their capabilities won’t match expectations.

Yet, despite all that, Donepudi remains interested and excited about the potential — and committed to being an early adopter: “My wife and I agreed that we’re going to buy the first one that comes out.”