IBM CEO Arvind Krishna Says AI Is Not A Bubble — But Warns Of Trillions In Overinvestment

IBM CEO Arvind Krishna has been around long enough to know how technology evolves and how it can benefit companies. Since taking over as the top executive of IBM in 2020, he has architected the strategic overhaul of the company, refocusing its direction towards hybrid cloud, enterprise software and artificial intelligence.

With the artificial intelligence (AI) boom, there is no question that IBM has repositioned itself as an infrastructure and services provider for large organisations transitioning towards AI. This has reshaped IBM's role in modern technology, with most companies increasingly investing in large-scale AI deployments, cloud infrastructure and enterprise solutions.

While that speaks well for Krishna and IBM, he cautions that despite AI's surging demand and popularity, it does not automatically guarantee success or significant returns. He explains why AI should not be seen as a speculative bubble, adding that everything depends on the scale and pace of capital being committed to support it.

'I have been accused sometimes of saying that it's not a bubble,' Krishna said in an interview with Nicolai Tangen on the Good Company podcast. 'Some will disappoint, many will thrive. But not all will thrive.'

Returns From AI Investment Not Immediate

It is a given that most companies are leaning towards AI technology with hopes of improving performance. Most project higher revenue with the adoption of artificial intelligence models, which at the same time could help bring down expenses.

Krishna is fully aware of this practice, citing the huge spending on AI data centres and semiconductors. By his estimates, a single gigawatt of AI data centre capacity requires between $60 billion and $80 billion worth of chips. Multiplying that by the hundreds of gigawatts needed for AI buildouts, the potential capital expenditure is projected to be between $6 trillion and $8 trillion.

With those numbers, Krishna points out how companies need to generate an additional $1 trillion to $2 trillion in incremental annual revenue over a five-to-seven-year period to recover those expenses. In his opinion, recovering from that huge spending is likely to take more time.

'If you say that that's got a seven-year payback, you are going to need an extra 1 to 2 trillion a year of revenue. Because inside that one to two, even if it is high margin, would be 20 to 30%. So that much incremental revenue, I don't believe is there,' Krishna explained.

Misreading AI Models and the Market

With AI, most companies feel that shifting to this technology would be good for their business. Krishna admits that this may hold true, but not for all. For the IBM CEO, some organisations have failed to consider the financial implications surrounding AI technology, adding that some capital markets are behaving as if demand, pricing power and long-term market structure are already settled.

Moreover, it also raises concerns about the evolution and effects of artificial intelligence over time. Krishna believes many organisations think that keeping abreast of current advances would help keep them competitive.

Krishna believes that for companies to benefit, the business outlook should be evaluated using long-term projections. Depending on the competitive nature of an industry, it is a given that not all companies transitioning to AI will reap the benefits of this technological change.

In his eyes, Krishna believes it is unlikely that more than two or three companies will achieve success in building and sustaining leading AI models. Despite the huge investments, the technology arguably comes with risk, something that could force companies to resort to alternative means to cut down on unforeseen expenses associated with adopting AI.

Hence, another element to consider aside from the staggering investment is the time organisations have set to realise returns. The answer will vary, depending on the niche a business operates in. Regardless, it remains possible that companies shifting to this new business philosophy may not reap those rewards for several years.