Artificial intelligence is poised to change everything, or so the multi-trillion-dollar story goes. Yet, for all the talk of a productivity revolution, a sobering analysis from Apollo Global Management finds scant proof of a widespread profit boom.
The Sobering Reality
According
to Torsten Slok, chief economist at investment firm Apollo, the massive investments in AI have delivered 'zero financial payoff' to American corporations outside of a few tech behemoths. The analysis highlights a stark divide in the US economy. While a handful of tech giants—often called the 'Magnificent Seven'—are seeing their revenues and profit margins soar, the story is very different for the rest of the market. Slok's research separates the S&P 500 into two groups: the Magnificent Seven (companies like Alphabet, Microsoft, and Nvidia) and the 'S&P 493', which represents the vast majority of mainstream businesses. The data shows that for these 493 firms, key metrics like revenue per worker and profit margins have remained flat, showing no discernible boost from AI. This has led some companies to start viewing AI spending less as a guaranteed source of growth and more as a cost center that eats into already tight margins.
A Tale of Two Economies
The findings from Apollo paint a picture of a two-speed economy. In one lane, you have the tech titans that build and deploy AI at scale. Their revenue per employee has jumped significantly since 2022, climbing from around $550,000 to nearly $800,000. In the other lane, the rest of corporate America is stuck in traffic, with its revenue per worker holding steady. This isn't just about revenue; it's about profitability. The profit margins for the tech leaders have continued to widen, while margins for the S&P 493 have stagnated at around 10%. The real test of the AI revolution, as Slok argues, will not be decided by the handful of companies selling the technology, but by the hundreds of other businesses that are supposed to be using it to become more efficient and profitable. So far, the evidence of that transformation is missing in action.
Echoes of Past Revolutions
This delay between a technology's arrival and its impact on productivity isn't new. Economists refer to it as the 'productivity paradox'. In 1987, Nobel laureate Robert Solow famously said, 'You can see the computer age everywhere but in the productivity statistics'. A similar pattern may be unfolding with AI. Implementing a truly transformative technology isn't like flipping a switch. It requires more than just buying software; it demands rethinking business processes, retraining entire workforces, and making significant organizational changes. Some studies on AI adoption have even shown a short-term dip in productivity—a 'J-curve' effect—as companies struggle with initial implementation before eventually seeing long-term gains. This is especially true for older, more established firms that may have to unlearn old habits.
Why The Lag?
There are several theories for why the AI boom hasn't lifted all boats. For one, Slok notes that business success relies heavily on human judgment, an area where AI still falls short. He points out that AI 'does not understand accountability, trust, culture, unwritten rules, ethical trade_offs or fairness', all of which are critical for managing risk and driving long term growth. Furthermore, many mainstream companies are unwilling to pay for the latest, most expensive AI models, seeing them as overkill for their current needs. While some research from firms like BCG indicates that nearly half of companies are starting to see value from AI, the broad macroeconomic data has yet to reflect a decisive shift. The consensus is that while a few firms are reporting specific, AI driven margin improvements, this hasn't yet translated into an economy wide surge.
