The Core of the Claim
Torsten Slok, chief economist at the investment giant Apollo, argues that the financial benefits of the AI boom are almost entirely concentrated within a small group of tech giants. He separates the S&P 500 into two groups: the 'Magnificent Seven' (think
Alphabet, Microsoft, Nvidia, etc.) and the remaining 493 companies. His analysis shows that while revenue per worker and profit margins are soaring for the Mag 7, these metrics have remained flat for everyone else. Essentially, Slok states that despite massive investment, there is no evidence that AI is improving revenue or profitability for the vast majority of corporate America.
The Productivity Paradox
A key part of Slok's argument is the absence of a broad productivity boom that was widely expected to accompany AI adoption. This echoes a historical economic concept known as the 'productivity paradox', where transformative new technologies—like the electric motor or the personal computer—took decades to show up in national productivity statistics. The same appears to be happening with AI. While many individual employees report feeling more productive using AI tools, this isn't translating to better overall company performance or profit. Instead of creating more free time, AI seems to be leading to higher output expectations and even longer hours for some workers.
A Cost Center, Not a Growth Driver
For many businesses outside of Big Tech, AI is starting to look less like a magic bullet for growth and more like a significant expense. Slok notes that mainstream companies are pulling back on spending for the most advanced AI models, viewing them as a cost center that eats into profit margins rather than a reliable source of new revenue. This is because, unlike the tech giants who build and sell AI, most firms are simply consumers of the technology, and the costs of using it at scale—often priced per 'token' or unit of data processed—can be enormous. Spending is highly concentrated, with a recent analysis showing the top 10% of firms accounting for over 95% of spending on major AI platforms.
The Human Judgment Factor
Slok also points to a fundamental limitation of the technology itself. He argues that AI, in its current form, cannot replicate the uniquely human aspects of business that drive long term success. Business intelligence relies heavily on judgment, which is shaped by context. AI, he states, 'does not understand accountability, trust, culture, unwritten rules, ethical trade_offs, or fairness'. These elements are critical for managing reputational risk, building customer loyalty, and ultimately, growing revenue and profits—areas where human oversight remains irreplaceable.
What This Means for India
This debate has direct relevance for India's massive technology sector and broader economy. A recent PwC India survey highlighted a similar trend, finding that 84% of Indian fintech companies had not yet seen measurable financial results from their AI investments, even as they continue to prioritize it strategically. For India's world leading IT services firms, the pressure is on to demonstrate a clear return on investment for their clients' AI projects. Slok's analysis suggests the path to profitability will be determined not by the technology's potential alone, but by how well the 'S&P 493'—the mainstream global businesses—can integrate it to create tangible value.
