Apollo Chief Economist Flags AI’s Uneven Payoff
TREE NEWS reports: Apollo Global Management’s chief economist, Torsten Slok, has thrown cold water on the idea that artificial intelligence is already transforming corporate America. In a note to clients, Slok observed that while the seven largest technology companies are seeing revenue per employee climb, the other 493 members of the S&P 500 have shown no such improvement. Profit margins tell a similar story, and there is little evidence that AI is yet driving measurable productivity gains across the broader economy.
Slok also highlighted a shift in corporate behavior: mainstream US companies are beginning to treat spending on AI token consumption as a cost center rather than a growth driver, as those expenses pressure margins. The comments come as the earnings season gets underway, with investors laser-focused on AI capital expenditure and whether it will generate the promised returns.
Why This Matters for Crypto’s AI Narrative
The crypto market has spent much of the past two years pricing in an AI future. Tokens tied to decentralized compute networks, GPU marketplaces, on-chain AI agents, and data provenance protocols have attracted billions in speculative capital, often on the thesis that AI adoption will be broad, rapid, and monetizable. Slok’s data challenges the speed and breadth of that adoption outside the hyperscaler elite.
For crypto AI projects, the implication is twofold. First, enterprise demand for decentralized compute and inference may ramp more slowly than token prices imply, particularly if CFOs tighten budgets around AI spending. Second, the distinction between AI infrastructure that serves crypto-native use cases and AI infrastructure that competes with AWS and Azure becomes critical. Projects that can demonstrate real revenue from non-speculative customers will stand out; those reliant on token incentives and circular DeFi yield may struggle.
Token Consumption as a Cost Center
Slok’s observation that firms now view AI token spending as a cost center is particularly relevant for crypto tokens that derive value from inference or compute consumption. If enterprises treat these costs as overhead to be minimized rather than growth investments to be scaled, demand for pay-per-token decentralized compute could face headwinds. Crypto projects will need to prove cost advantages, not just decentralization benefits, to win enterprise budgets.
Forward Look
The coming earnings season will be a reality check for the AI trade broadly, and by extension for crypto’s AI-adjacent tokens. Investors should watch for guidance on AI spending from non-tech S&P 500 companies and for any signs of margin compression tied to AI costs. For crypto AI protocols, the path forward lies in demonstrable, non-incentivized usage and integration with real business workflows. Until then, the gap between narrative and adoption—already visible in traditional markets—may also weigh on digital-asset valuations.
