Beware the Great AI Bubble Popping – Source: www.databreachtoday.com

Artificial Intelligence & Machine Learning
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Next-Generation Technologies & Secure Development

Crashing Markets, Slower Innovation, But More Sustainable AI Development

Rashmi Ramesh (rashmiramesh_) •
September 18, 2024    

If the bubble isn’t popping already, it’ll pop soon, say many investors and close observers of the artificial intelligence industry.

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The thing about bubbles is that they’re best seen in retrospect – especially since from the inside of one, reality is curved and distorted. So, it’s hard to say for certain. But whether the industry is in a bona fide bubble or not, there does appear to be a clear disconnect between the market’s perception of value and the economic reality. It’s a pattern seen in past bubbles in tech that span the dot-com crash to the crypto industry collapse.

In each case, unrealistic expectations inflated valuations, and when the enthusiasm died down, overvalued assets crumbled, leaving investors with losses. Bubbles have a common storyline: fast-paced growth driven by speculative investing, followed by sharp downturns.

In AI’s case, several companies in the industry saw the value of their stocks skyrocket in the past year. Chip designer Nvidia is the prime example – its stock more than tripled since last summer. Tech giants such as Google and Microsoft, which have invested heavily in AI, also saw large increases. Venture capitalists invested $2.71 billion into AI in the second quarter this year, making up half of all VC investments in the period, PitchBook data shows.

Unprecedented leaps in stock prices, especially with little evidence of real-world application of the technology, are often indicators of an overdue market correction. Goldman Sachs, which once estimated that up to 50% of jobs would be exposed to automation, updated its outlook to say that the technology has not progressed enough yet to replace jobs at the rate of its earlier prediction.

MIT labor economist Daron Acemoglu estimated that productivity gains from AI will be less than 1% in the next decade, and venture capitalist David Kahn of Sequoia Capital said that firms need to bring in about $600 billion in revenue to make good on their AI bets.

So the question is: What happens when the AI bubble does burst?

If the past bubbles are a benchmark, the burst will filter out companies with no solid business models and pave the way for more sustainable growth for the industry in the long term – but not before causing pain for investors, the U.S. economy, companies in the industry and their employees in the short term.

AI struggled to make profits this year despite the seemingly bottomless investments and deep expectations. The reason: AI companies spent the cash infusions on recurring expenses such as data centers, computing hardware such as GPUs, and large language model training. The resulting products, such as chatbots and image generators, are barely monetized, as they’re considered add-on features and not platforms in their own right. Microsoft’s Copilot is part of the Windows operating system, and Apple Intelligence is integrated into the iPhone maker’s products. At the moment, neither requires users to pay separately. OpenAI does offer freemium access to its AI services at nominal prices as a means to generate revenue.

This does not mean that the technology will never make money. Early stages of evolution in any tech usually involve trying products in the market by making them as accessible as possible and monetizing the solutions when there’s clarity on use cases, sizable adoption, dependency and demand. Generative AI will take a while longer to get there.

The Great Popping will also lead to the ecosystem thinning. Startups with speculative or unsustainable business models will shutter shop as funding decreases. The most likely future scenario is that the AI landscape will shift to make room for a small number of long-term players that focus on practical applications, while the rest go bust.

Despite sharing similarities with the dot-com bubble, the residue of the AI one will likely differ in that entire companies, especially the OpenAIs and the Anthropics, won’t likely shutter completely. They may close down money-guzzling units, rejigger focus or even pivot entirely, but they are unlikely to vanish off the face of the earth as their dot-com counterparts did.

Job losses are a likely inevitability, and few firms will hire the laid-off employees. Fewer minds researching and developing the technology may also potentially slow down progress. Industries that are now quickly adopting AI, such as healthcare, finance and manufacturing, could become more cautious, potentially delaying productivity gains.

In addition to AI companies themselves, suppliers of tools and hardware to these companies will also be affected. Without a bottomless wallet, companies will not find it cost-efficient to train large language models, paving the way for more focused, smaller, open-source models.

History has shown that shakeouts often pave the way for sustainable evolution of the technology. That said, nobody can truly predict the future.