AI delivers ‘zero financial payoff’ to most companies, Apollo economist says

AI investments have yet to show a profit for businesses outside of the tech industry.

AI has not delivered a demonstrable financial return to most U.S. corporations outside the technology sector, according to Torsten Slok, chief economist at Apollo Global Management. Slok analyzed the S&P 493 – the S&P 500 excluding major tech firms like Alphabet, Amazon, Apple, Meta, Microsoft, Nvidia, and Tesla. His findings indicate that profit margins and revenue per worker for these companies have remained stagnant, showing no discernible improvements attributable to AI investments. Slok expressed skepticism about non-tech companies' ability to translate AI into substantial revenue growth or increased profit margins. He argued that while AI can perform calculations, business intelligence largely relies on judgment, which AI currently lacks, particularly concerning accountability, trust, culture, unwritten rules, ethical trade-offs, and fairness – elements crucial for managing reputational risk and driving financial success. Previous research has also suggested that AI has not yet yielded significant productivity gains across industries.

The analysis from Apollo's chief economist suggests that the current applications of AI are insufficient to overcome fundamental business challenges related to judgment and strategic decision-making. This implies that the 'AI revolution' may require more than just computational power; it necessitates the integration of AI into complex human-centric processes. Companies looking to leverage AI for financial gains will need to focus on how the technology can augment human judgment rather than replace it, particularly in areas that manage reputational risk and drive long-term growth. The findings highlight a potential disconnect between the hype surrounding AI capabilities and its practical, bottom-line impact in diverse business environments.

This outlook challenges the widespread assumption that AI adoption will automatically lead to productivity and profitability across all sectors. For non-tech companies, it means that focusing solely on acquiring AI tools may not be enough; strategic implementation that aligns with unique business contexts and human expertise is paramount. The economic reality presented suggests that the path to AI-driven financial success for many businesses may be longer and more nuanced than anticipated. Investors and executives should temper expectations and prioritize use cases where AI can demonstrably enhance judgment-based decision-making and mitigate inherent business risks, rather than expecting immediate, broad-based efficiency gains.