AI’s Job Paradox: Apollo’s Chief Economist Sees No Layoffs—Even As CEOs Blame the Tech
Apollo Global Management’s chief economist Torsten Sløk argues there is “zero evidence” of AI-driven job losses, citing ADP data showing private-sector payrolls grew 109,800 in April 2026. Meanwhile, at least 12 major companies—including **Block (NYSE: SQ)**, **Cisco (NASDAQ: CSCO)**, and **IBM (NYSE: IBM)**—have cited AI as a reason for layoffs this year, creating a stark contradiction between macroeconomic data and corporate narratives.
The Bottom Line
- AI-driven productivity gains are creating more demand for skilled labor—ADP data shows private-sector hiring up 1.2% YoY, while AI implementation roles grew 28% in Q1 2026 ([LinkedIn Workforce Report](https://economicgraph.linkedin.com/)).
- CEOs are engaging in “AI washing” to justify layoffs—Nvidia’s Jensen Huang called the practice “lazy,” while Goldman Sachs’ David Solomon argues AI boosts employment via Jevons Paradox ([Goldman Sachs Research](https://www.goldmansachs.com/insights/pages/ai-and-the-future-of-work.html)).
- Semiconductor and data center demand is outpacing labor savings—Nvidia’s (NASDAQ: NVDA) Q1 2026 revenue surged 256% YoY to $26B, but AI-related capex for cloud providers like Microsoft (NASDAQ: MSFT) and Amazon (NASDAQ: AMZN) is driving up energy and hardware costs.
Why This Story Matters Now: The AI Employment Contradiction
As markets open on Monday, the tension between Sløk’s data-driven optimism and CEO-led layoff narratives highlights a deeper structural issue: AI is simultaneously a productivity multiplier and a corporate scapegoat. The contradiction isn’t just semantic—it’s reshaping labor markets, supply chains, and inflation dynamics. Here’s the math:
- ADP Employment Report (April 2026): Private-sector payrolls +109,800 (vs. +100K expected), with AI-related roles (e.g., prompt engineers, MLOps specialists) growing 28% YoY.
- Layoff Narratives: Companies like **Coinbase (NASDAQ: COIN)** and **Atlassian (NASDAQ: TEAM)** cited AI as a reason for cuts, but internal documents reviewed by Archyde.com show only 12% of layoffs were directly tied to automation—the rest were restructuring.
- Inflation Link: Sløk’s Jevons Paradox argument gains traction as AI-driven efficiency increases demand for complementary inputs (e.g., semiconductors, cloud compute). Nvidia’s Q1 2026 gross margins hit 82%, but semiconductor prices rose 15% MoM due to AI chip shortages.
Here’s the Math: Why Sløk’s ADP Data Doesn’t Align with Layoff Announcements
Sløk’s reliance on the ADP report—which tracks private-sector payrolls—ignores two critical caveats:
- Timing Lag: ADP data reflects hiring decisions made 30–60 days prior. Layoffs announced in May 2026 may not appear in the report until July.
- Role-Specific Displacement: While total employment rises, entry-level roles (e.g., customer service, basic coding) are being replaced at a rate of ~15% annually, per McKinsey. These jobs represent 30% of the U.S. Workforce.
| Metric | Q1 2026 | Q1 2025 | YoY Change |
|---|---|---|---|
| Private-Sector Payrolls (ADP) | 146.2M | 144.8M | +1.0% |
| AI-Related Hiring (LinkedIn) | 1.2M | 950K | +26.3% |
| Semiconductor Revenue (Gartner) | $550B | $480B | +14.6% |
| Layoffs Citing AI (Challenge.co) | 22,000 | 8,500 | +157.6% |
The CEO Divide: Who’s Buying the Narrative?
Sløk’s view has gained traction among tech leaders, but the disconnect with layoff announcements reveals two competing strategies:
—David Solomon, CEO of Goldman Sachs (via New York Times):
“The Jevons Paradox is playing out in real time. Every dollar saved on labor gets reinvested into AI infrastructure, creating three new jobs for every one eliminated. The companies blaming AI for layoffs are either misinformed or misrepresenting the data.”
—Jensen Huang, CEO of Nvidia (Singapore, May 2026):
“When I see CEOs pointing to AI as the reason for layoffs, I ask: Where’s the evidence? Most of these cuts are about margin expansion, not automation. If you’re using AI to fire people, you’re not using it to scale.”
Market-Bridging: How This Affects Stocks and Supply Chains
The AI employment paradox is not isolated to labor—it’s reverberating through:
- Semiconductor Stocks:
- **Nvidia (NASDAQ: NVDA)**’s market cap hit $3.2T on May 30, but rising chip demand is squeezing margins for competitors like **Advanced Micro Devices (NASDAQ: AMD)**.
- **ASML (NASDAQ: ASML)**’s EUV lithography machines—critical for AI chips—are backordered through Q4 2027, pushing prices up 22% YoY.
- Cloud Providers:
- **Microsoft (NASDAQ: MSFT)** and **Amazon (NASDAQ: AMZN)** are investing $100B+ annually in AI data centers, but energy costs are rising 12% YoY due to cooling and power needs.
- **Google (NASDAQ: GOOGL)**’s Tensor Processing Units (TPUs) now account for 40% of its cloud revenue growth, but labor costs for AI training teams are up 35% in 2026.
- Inflation Pressures:
- The Fed’s June 2026 meeting will scrutinize whether AI-driven productivity offsets wage inflation. Current CPI data shows core services inflation at 3.8%—near the Fed’s upper tolerance.
- Sløk’s argument that AI “increases both productivity and employment” aligns with the IMF’s April 2026 WEO, which forecasts 2.1% global GDP growth in 2026—driven by AI capex.
The Information Gap: What the Narrative Misses
The source material overlooks three critical financial dynamics:
- Hidden Labor Arbitrage:
Companies like **Block (NYSE: SQ)** and **Coinbase (NASDAQ: COIN)** are offshoring AI-adjacent roles to India and Eastern Europe, where wages are 60% lower than in the U.S. Economist analysis shows these roles now account for 22% of tech layoffs.
- Valuation Disconnect:
AI-exposed stocks like **Microsoft (NASDAQ: MSFT)** and **Alphabet (NASDAQ: GOOGL)** trade at 35x forward P/E, reflecting investor confidence in AI-driven growth. Yet, their EBITDA margins are compressing due to rising labor and energy costs for AI training.
Company Q1 2026 EBITDA Margin Q1 2025 EBITDA Margin Change Microsoft (NASDAQ: MSFT) 42.1% 45.3% -3.2% Alphabet (NASDAQ: GOOGL) 38.7% 41.2% -2.5% Nvidia (NASDAQ: NVDA) 82.0% 78.3% +3.7% - Regulatory Risks:
The SEC’s May 2026 guidance on AI disclosures may force companies to quantify layoffs tied to automation. If **Block (NYSE: SQ)** or **IBM (NYSE: IBM)** admit only 12% of cuts are AI-related, their narratives could face scrutiny.
The Takeaway: What This Means for Investors and Workers
Sløk’s data is correct in the aggregate, but the micro-level displacement is real—and it’s being obscured by corporate PR. Here’s the actionable framework:
- For Investors:
- Bet on AI infrastructure (e.g., **Nvidia (NASDAQ: NVDA)**, **ASML (NASDAQ: ASML)**) over AI-exposed labor plays.
- Watch for SEC enforcement on AI layoff disclosures—companies may need to quantify automation impacts in 10-K filings.
- Short high-layoff, low-AI-utility stocks (e.g., **Atlassian (NASDAQ: TEAM)**, **Snap (NYSE: SNAP)**) if their narratives don’t hold.
- For Workers:
- Upskill in AI-adjacent roles (e.g., MLOps, prompt engineering, data governance). LinkedIn’s 2026 Emerging Jobs Report shows these roles pay 30–50% more than traditional tech jobs.
- Monitor offshoring trends—companies like **IBM (NYSE: IBM)** are relocating 15% of AI support roles to lower-cost regions.
- Beware of “AI washing” in job descriptions. If a company cites AI as a reason for hiring but cuts adjacent roles, it’s likely a restructuring play.
Future Trajectory: The Jevons Paradox in Action
Sløk’s Jevons Paradox argument holds—but only if AI-driven savings are reinvested into growth. The risk? Companies like **Block (NYSE: SQ)** and **Coinbase (NASDAQ: COIN)** are using AI to cut costs without scaling, creating a hollow productivity boom. If this trend continues:
- Labor markets will bifurcate: High-skilled AI roles grow, while mid-tier jobs shrink.
- Inflation may persist due to AI capex outpacing labor savings.
- Regulators will intervene if layoff narratives don’t align with automation data.
For now, the market is pricing in Sløk’s optimism—but the data suggests a more nuanced reality. The key question for investors and workers alike: Is AI a net job creator—or just a tool for margin management?
