The buzz around Artificial Intelligence has been deafening, with promises of a revolution in productivity and profit. But a top economist is pouring cold water on the hype, arguing the AI boom is not what it seems. Here's what you need to know.
The Economist Behind the Claim
The analysis
comes from Torsten Slok, the chief economist at Apollo Global Management, a major global investment firm. His notes and charts are widely followed on Wall Street for their data-driven insights. Recently, Slok released a research note that quickly captured the market's attention with a bold declaration: AI has so far delivered 'zero financial payoff' to most companies outside of the tech sector. This assessment directly challenges the prevailing narrative that AI is already transforming the broader economy.
The Great Divide: Mag 7 vs. S&P 493
Slok's central point is a stark divergence in the market. He separates the S&P 500 index into two groups: the 'Magnificent Seven' (tech giants like Alphabet, Amazon, Microsoft, and Nvidia) and the remaining 493 companies. His data shows that since 2022, key metrics like revenue per worker and profit margins have soared for the Mag 7. However, for the other 493 companies, those same metrics have remained flat. In essence, the financial benefits of the AI gold rush are being concentrated in the hands of the few companies selling the technology, not the many companies buying it.
No Productivity Boom… Yet
One of the biggest promises of AI is a massive leap in productivity across all industries. However, Slok's analysis finds no clear evidence of this happening on a broad scale. Despite massive capital investment in AI infrastructure, the expected efficiency gains and boosts to output are not showing up in the economic data for most of the market. This suggests that while companies are spending heavily on AI, they are struggling to translate that spending into measurable improvements to their bottom line, leading many to view AI spending as a cost centre rather than a growth driver.
The Problem of High Costs
Implementing AI is incredibly expensive. The cost of computing power, specialised chips, energy consumption, and talent is enormous. Tech giants are investing hundreds of billions of dollars to stay competitive, putting a strain on even their massive cash flows. For 'mainstream corporate America', Slok argues, the latest and most powerful AI models are often not needed and the high cost is a major deterrent. Many companies are reportedly pulling back on spending, unwilling to pay for frontier models when the return on investment is not clear. This creates a risk that the trillions being spent on AI infrastructure may not be justified if widespread demand fails to materialise.
Echoes of Bubbles Past?
Slok's analysis has intensified fears of an AI bubble reminiscent of the dotcom era of the late 1990s. During that period, companies were valued based on hype and potential rather than actual profits, leading to a massive market correction. The current situation shows some parallels, with a circular flow of investment where big tech companies invest in each other and in AI startups, potentially inflating valuations. While some analysts argue today's market leaders are far more profitable than dotcom companies were, the core question remains : can the immense spending be sustained if profits don't spread to the wider economy?
A Reality Check for Indian Firms
This global analysis holds important lessons for India's burgeoning tech industry. Indian firms , from startups to established IT giants , are also investing heavily in AI capabilities . A recent survey noted that a significant majority of Indian fintech firms had yet to see measurable financial results from their AI investments . Slok’s cautionary note suggests that Indian business leaders should also prioritise a clear path to profitability . The focus should be on practical applications that solve realworld problems and generate tangible returns , rather than adopting AI simply for the sake of it . The true test will be turning technological potential into sustainable business value .
