IBM's CEO says AI industry isn't a bubble, but a race for 7.5 billion subscribers worldwide

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IBM CEO Arvind Krishna rejects fears of an AI bubble, arguing the industry mirrors social media's evolution where a few winners emerged from many competitors. Speaking on The Verge's Decoder podcast, he explains that success depends on capturing subscribers at scale, though he acknowledges uncertainty about which companies will ultimately dominate the market.

IBM CEO Rejects AI Bubble Concerns in Candid Industry Assessment

Arvind Krishna, IBM CEO, has pushed back against widespread concerns that the AI industry is heading toward a bubble burst. In a recent appearance on The Verge's Decoder podcast with editor-in-chief Nilay Patel, Krishna argued that the current AI landscape resembles previous technology cycles rather than an unsustainable bubble

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. His perspective adds nuance to a debate that often swings between extreme pessimism and unbridled optimism about artificial intelligence's future.

Source: Seeking Alpha

Source: Seeking Alpha

The IBM executive explicitly stated there is no AI bubble, though he acknowledges some risks around debt capital funding AI growth

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. His explanation focuses on how technology markets typically evolve, with multiple competitors vying for dominance and only a few emerging as winners.

The Race for Subscribers and Network Scale

Krishna frames the AI industry competition as fundamentally about capturing users at massive scale. "This is a race towards who can get more and more of the world's 7.5 billion people to become subscribers of a given model," he explained, drawing parallels to social media's evolution

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. The comparison highlights how economies of scale and network scale become critical factors determining which companies survive and thrive.

This subscriber-focused model suggests that AI companies must achieve widespread adoption to justify their valuations and capital expenditures. The IBM CEO's framing shifts the conversation from whether AI itself has value to which companies can successfully monetize that value through user acquisition.

Uncertainty About Market Winners and Capital Returns

While Krishna maintains the AI industry is not a bubble, he admits significant uncertainty about which companies will ultimately succeed. He acknowledged that some current capital expenditures appear difficult to recoup, requiring "hundreds of billions of profit just to pay for the interest"

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. When discussing OpenAI CEO Sam Altman's confidence in achieving these returns, Krishna characterized it as "a belief" that one company could capture the entire market.

The IBM CEO suggested that while some investors will profit and others will lose money, the industry pattern resembles previous technology cycles like the dot-com boom and social media. In those cases, a small number of companies emerged as dominant players while many others failed, but the technology itself proved transformative and valuable.

Technology Cost Reductions Expected Over Five Years

Krishna expressed optimism about dramatic cost reductions in AI technology, projecting a 1,000-times decrease in costs over the next five years. He broke down this projection into three components: a 10x improvement from silicon advances, another 10x from design innovations, and a third 10x from software optimization including memory caching and model deployment strategies

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. These efficiency gains could fundamentally alter the economics of AI deployment and make services more accessible to broader audiences.

Such cost reductions would address one of the key concerns fueling AI bubble fears: whether companies can deliver services profitably at scale. If Krishna's projections prove accurate, the path to sustainable business models becomes clearer.

Skepticism About AGI and Focus on Quantum Computing

Krishna views the odds as extremely low, between 0-1%, that current technology will lead to Artificial General Intelligence (AGI), emphasizing that breakthroughs beyond today's large language models would be required

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. This measured stance on AGI contrasts with more ambitious predictions from some AI industry leaders.

Meanwhile, IBM sees quantum computing as offering significant optionality, expecting quantum processors to solve currently intractable problems and drive high-margin software growth and strong free cash flow

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. This focus on quantum represents IBM's bet on innovation beyond conventional AI approaches. Following the podcast, BofA maintained its Buy rating and $315 price target on IBM stock, suggesting confidence in the company's strategic positioning

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