Gartner has joined the growing chorus of companies, institutions, and investors warning that artificial intelligence may never realize the promise its proponents hold out.
AI has taken the tech world by storm, with companies large and small investing billions to advance Generative AI (GenAI) models and try to be the first to crack Artificial General Intelligence (AGI), AI that can truly rival human intelligence. Unfortunately for companies, AI development has been plagued with runaway costs; seemingly unfixable hallucinations; legal and ethical issues surrounding copyright and content ownership; and the digital equivalent of mad cow disease.
Financial institutions have increasingly been warning that AI may never live up to the hype, and could represent the latest tech bubble on the verge of bursting. Gartner has now weighed in, joining the chorus of organizations voicing concern over the future of the tech.
In an interview with The Register, Gartner analyst Arun Chandrasekaran said clients were focused on GenAI, investing billions to achieve. Nonetheless, such organizations were about to experience the “trough of disillusionment.”
“The expectations and hype around GenAI are enormously high,” Chandrasekaran added. “So it’s not that the technology, per se, is bad, but it’s unable to keep up with the high expectations that I think enterprises have because of the enormous hype that’s been created in the market in the last 12 to 18 months.”
Chandrasekaran says there is a place for GenAI, but that the hype surrounding it has oversold what it can do, especially in the short-term.
“I truly still believe that the long-term impact of GenAI is going to be quite significant, but we may have overestimated, in some sense, what it can do in the near term.”
Because of the issue with GenAI, including “no robust solution to hallucinations,” “modest lasting corporate adoption,” and “modest profits,” Chandrasekaran believes the seemingly unlimited hose of cash being directed at GenAI will soon dry up.
“To be sure, Generative AI itself won’t disappear,” Chandrasekaran explained. “But investors may well stop forking out money at the rates they have, enthusiasm may diminish, and a lot of people may lose their shirts. Companies that are currently valued at billions of dollars may sold, or stripped for parts.”
Others Have Voiced Similar Concerns
Chandrasekaran’s observations echo those of Goldman Sachs Head of Global Equity Research Jim Covello. In a report in July, Covello pointed out the cost difference between AI and previous disruptive technologies, like the Internet. In past cases, low-cost tech was disrupting far more costly existing solutions. In the case of AI, it’s the exact opposite, with one of the most expensive technologies in history trying to disrupt much cheaper options.
Covello makes the case that AI’s ability is nowhere near where it needs to be to justify that cost:
Many people attempt to compare AI today to the early days of the internet. But even in its infancy, the internet was a low-cost technology solution that enabled e-commerce to replace costly incumbent solutions. Amazon could sell books at a lower cost than Barnes & Noble because it didn’t have to maintain costly brick-and-mortar locations. Fast forward three decades, and Web 2.0 is still providing cheaper solutions that are disrupting more expensive solutions, such as Uber displacing limousine services. While the question of whether AI technology will ever deliver on the promise many people are excited about today is certainly debatable, the less debatable point is that AI technology is exceptionally expensive, and to justify those costs, the technology must be able to solve complex problems, which it isn’t designed to do.
AI’s day of reckoning may be fast approaching, with the companies pushing to develop it forced to justify its cost or come up with some other way to continue funding its development.
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