Tech execs are adamant the AI craze is not a bubble, despite the vast sums of money being invested, overinflated valuations given to AI startups, and reports that many projects fail to make it past the pilot stage.
HPE is one of the giants tapping into booming demand for high-performance hardware to drive AI development, and the president and general manager of its Networking division, Rami Rahim, told us he doesn’t see that ending anytime soon.
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“It wouldn’t be the first time in the history of this industry that there would be a correction, and that’s fine, you know. So we would adjust, and we would be just fine in the end. But I don’t see it at this point in time. Right now, I don’t see any signs of a slowdown based on the projects that are in the market right now and the conversations and the plans that we’re talking about with our customers,” he said.
Rahim was speaking to The Register at HPE’s Discover event in Barcelona this week, where it showcased various new and upcoming technologies, most with an AI twist.
Asked about many AI projects not making it into production, he said: “There are pilots, but I also think there’s a lot of actual, real value being created with production products. I mean, I can tell you from the standpoint of what we do in engineering inside of HPE Networking, more and more of our developers are getting far more efficient by leveraging copilots to write software and to verify software.”
But aren’t there concerns about the quality of the code produced by AI assistants?
“In the early days, there was a lot of concern, but I’ve seen an inflection point, the technology and trust based on more and more experience with it has actually improved dramatically. So it takes time. These things never happen overnight, but I sincerely do see the value,” Rahim said.
Many people have drawn parallels with the current situation and the dotcom market bust at the turn of the millennium, but Rahim said what is happening with AI right now is not completely analogous to what happened then.
“I don’t think it’s a good idea to look at the past as an indicator of what might happen in the future,” he told us.
“It’s just different technologies right now. I mean, right now, the appetite for consumption of AI products, GPU cycles, is enormous,” Rahim said. Whether that changes in a year or two is “difficult to say,” he admitted.
AMD chief exec Lisa Su also maintains that AI is definitely not a bubble.
Speaking at the UBS Global Technology and AI Conference 2025 this week, Su said: “I spend most of my time talking to the largest customers, the largest AI users out there. And there’s not a concept of a bubble.”
Instead, she believes the tech industry is a couple of years into a “ten-year super cycle,” one where “computing allows you to unlock more and more levels of capability, more and more levels of intelligence.”
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The cycle started with model training as the primary use case, but is now shifting to inference, Su noted, and with no single model fitting all situations and use cases, customers are having to fine-tune to meet their requirements, and this continues to drive demand for infrastructure.
“The one thing that is constant as we talk to customers is we need more compute. That at this point, if there was more compute installed, more compute capability, we would get to the answer faster,” Su claimed. As the head of a company that makes CPUs, GPUs, ASICs, and FPGAs, she would say that, of course.
But what of companies like the industry darling OpenAI, which is valued at $500 billion even though it doesn’t expect to make money until 2030 and may have to raise hundreds of billions to cover losses and its investments in AI datacenters?
“I think all of the capex forecasts that have increased over the last three to six months have certainly shown that there is confidence that those investments are going to lead to better capabilities going forward,” Su said.
“And so, from the standpoint of do we see a bubble, we don’t see a bubble. What we do see is very well-capitalized companies, companies that have significant resources, using those resources at this point in time because it’s such a special point in time in terms of AI learning and AI capabilities,” she added.
This is despite OpenAI CEO Sam Altman admitting earlier this year that he thinks the industry is in the midst of a bubble.
When asked about complaints from many early adopters that there is little or no return on the investments they have made in AI, Su claimed this has not been AMD’s experience.
“What started as, let’s call it, let’s try AI for our internal use cases, has now turned into significant clear productivity wins going forward. So there’s no question that there is a return on investment for investment in AI,” she said.
The Register has covered a number of situations where this has not been the case, such as this one, this one, this one, or this one.
Even Microsoft admitted it has more work ahead to convince customers of ROI.
Su did concede that AI has not lived up to all the hype being broadcast about it.
“If you look at today’s AI, as much progress as we’ve made over the last couple of years, we’re still not at the point where we’re fully exploiting the potential of AI,” she said.
“And I still say that we are in the very, very early innings of seeing that payoff. So as we talk to the largest enterprise customers, I think every conversation is, ‘Lisa, how can you help us, how can we learn faster so that we can take advantage of the technology?’ So I think the return on investment certainly will be there.”
Meanwhile, Microsoft was forced to deny reports this week which claimed several of its divisions had lowered growth targets for products using AI after sales staff missed goals for the fiscal year that ended in June.
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Elsewhere, the head of South Korean conglomerate SK Group, which owns memory chipmaker SK hynix, opined that AI stocks might be due a haircut after rising too fast and too high.
“I don’t see a bubble in the AI industry,” SK Group chairman Chey Tae-won said at a forum in Seoul, as reported by Reuters.
“But when you look at the stock markets, they rose too fast and too much, and I think it is natural that there could be some period of corrections,” he added.
This could come soon, according to research firm Forrester, which recently found that large organizations are set to defer a large chunk of planned AI spending until 2027 because of the current gap between vendor promises and reality.
Even the Bank of England’s Financial Policy Committee has warned of the dangers of a sudden correction in the financial markets because of AI stocks, comparing the risks to the dotcom bubble. ®