Torsten Slok, chief economist at Apollo Global Management, has analyzed the S&P 493—the companies in the S&P 500 excluding the so-called Magnificent Seven. His findings suggest that the financial benefits of artificial intelligence have so far been concentrated among major technology companies, including Tesla, Microsoft and Nvidia.
According to Slok, companies outside the technology sector have seen little measurable business benefit despite substantial AI investment and widespread enthusiasm around the technology. Revenue and profit margins in those industries have remained largely unchanged, apart from minor fluctuations.
The Magnificent Seven, by contrast, have recorded clear gains since the beginning of 2023. Revenue per employee has increased significantly and now stands well above the level reported by large companies outside the technology sector. Margins at companies such as Apple and Meta have risen to around 30 percent. Until 2020, they were roughly one-third of that level, according to the analysis.
Slok attributes the lack of progress elsewhere partly to the sharp rise in token consumption and the resulting costs. Companies are increasingly treating spending on tokens as an expense that puts pressure on margins rather than as a source of growth.
Businesses in Germany have also reported being surprised by high AI fees. In a Bitkom survey cited in the report, around one-third of companies said they had been affected by unexpectedly high costs. Some are responding by using different AI models for different tasks instead of relying on expensive top-tier models across the board.
This approach, sometimes referred to as modelmaxxing, has contributed to the emergence of model-routing startups. These companies automatically assign tasks to the model best suited to the job’s complexity while aiming to keep costs as low as possible.
In Slok’s view, the decisive test for AI will not be its impact on the Magnificent Seven, but whether the remaining S&P 493 can turn the technology into sustainable business gains. He argues that economic decision-making depends not only on computing ability but also on judgment, context, responsibility, trust, culture, ethical considerations and fairness—factors that can influence reputational risk, revenue growth and profit margins.
Sources: t3n.