Apollo's chief economist says he sees 'zero evidence' of AI-related job losses, even as CEOs cite the tech in layoffs

Apollo chief economist Torsten Sløk said there is "zero evidence of job losses because of AI," citing ADP data showing private payrolls rose by almost 110,000 in April. He argued that AI spending is boosting hiring, wages for AI specialists, semiconductor prices, equipment demand, and energy use, implying a modest inflationary tailwind. The article contrasts this with recent layoffs at companies including Block, Cisco, Atlassian, Cloudflare, Coinbase, IBM, and Snap that have cited AI as a factor.

Analysis

The market is likely underpricing the split between AI demand beneficiaries and AI labor-disruption headlines. In the near term, the strongest second-order effect is not broad labor substitution but margin transfer: AI implementation, data-center capex, and power/network bottlenecks should keep rent extraction elevated for the enabling stack, while software vendors with weak differentiation risk having to spend more just to prove they are AI-native. That argues for staying selective rather than treating AI as a uniform beta trade.

The most interesting signal is inflationary rather than disinflationary. If AI spend continues to pull forward semiconductor, networking, and electricity demand, then the “productivity boom” can coexist with sticky input inflation for 2-4 quarters, which matters for rate-sensitive software and small-cap growth. This is especially relevant if management teams start using AI as a credible justification for restructuring: the headline layoffs can compress near-term payrolls, but the spending side may keep earnings revisions bifurcated—better for hardware/infrastructure, worse for human-labor-intensive services.

The contrarian take is that consensus may be too focused on job displacement and not enough on implementation costs and adoption friction. Enterprises may buy AI but fail to monetize it quickly, creating a period of rising opex without commensurate revenue uplift. If that happens, the “AI winners” trade will rotate from application-layer optimism to picks-and-shovels and balance-sheet strength, while the broader AI basket de-rates as investors demand proof of ROI.

Catalyst-wise, watch the next 1-2 earnings seasons for commentary on AI-driven headcount productivity, capex intensity, and power procurement; that will tell us whether this is an earnings tailwind or just narrative support. The biggest reversal risk is a sudden slowdown in data-center orders or evidence that AI budgets are being cut into non-revenue-producing pilots, which would hit the infrastructure complex first and the labor market narrative second.

Key Decisions for Investors

• Long NVDA vs short TEAM/NET for 1-2 quarters: buy the infrastructure beneficiaries with pricing power and short the software names most exposed to AI spend scrutiny; target 10-15% relative outperformance if capex remains firm and enterprise ROI stays slow.
• Overweight DELL and GS on a 3-6 month horizon: both can benefit from enterprise capex, financing, and advisory activity around AI buildouts; use pullbacks to add with a 2:1 upside/downside profile versus broader tech.
• Short CSCO/IBM into earnings-rally strength for 1-3 months: these are the names most at risk if investors decide AI is accelerating hardware/software commoditization faster than management can offset with product refreshes; cover if guidance implies re-acceleration in orders.
• Own ADP as a modest long against cyclical labor-disruption fear over 2 quarters: if AI is driving more hiring of specialists and still-healthy payroll growth, payroll processors should remain resilient, with limited downside and mid-single-digit upside.
• Buy medium-dated NVDA call spreads funded by short-dated put spreads on software beta: expresses the view that AI spending stays inflationary and concentrated in the supply chain, while limiting bleed if the market rotates away from growth.