CEO of $1.25 billion AI company says he hires Gen Z because they’re ‘less biased’ than older generations—too much knowledge is actually bad, he warns

Ricardo Amper, founder and CEO of $1.25 billion identity-verification software company Incode Technologies, argues that hiring fresh, inexperienced Gen Z talent—balanced with older, emotionally mature staff—drives innovation in AI and tech. He cites his multi-decade founder track record and references peers like DeepSeek, a Gen Z-led Chinese AI firm, and Colgate-Palmolive ($62 billion) adopting young digital talent, implying companies that prioritize creative, unbiased hires may secure a competitive product-innovation edge while needing experienced hires for operational resilience.

Analysis

Market structure: Younger, AI-native teams (early-stage AI firms, identity verification startups like Incode) are the immediate beneficiaries; expect these firms to win share vs. slow-moving incumbents through 2024–2026 product cycles. Talent-driven supply shortage will bid up junior AI wages ~5–10% over the next 12 months, pressuring margins for small players but increasing valuations (price/sales premia +10–20%) for scalable, productized winners. Consumer incumbents that successfully integrate Gen Z digital skills (e.g., CL) gain asymmetric ROI via faster e-commerce growth and lower CAC.

Risk assessment: Tail risks include data-privacy regulation and cross-border talent restrictions (10–20% probability over 24 months) that could cut TAM for identity/AI firms by >15%. Short-term (0–3 months) risks are hiring-cost spikes and retention churn; medium-term (3–12 months) risks are failed scale/monetization; long-term (12–36 months) risk is consolidation if inexperienced teams cannot manage ops. Hidden dependencies: access to high-quality labeled data and senior mentorship; catalysts are model breakthroughs or large hiring waves from layoffs that can flip supply/demand rapidly.

Trade implications: Favor public plays that capture digital talent arbitrage without private-market execution risk: modest overweight in CL (consumer staples with digital upside) and underweight legacy financials (GS) that may be slower to adapt culturally. Implement pair trades (long CL, short GS) and targeted options to express asymmetric risk/reward—use durations 3–12 months tied to quarterly hiring/earnings signals. Rotate into cybersecurity/identity names if regulatory clarity is neutral and retention metrics exceed thresholds.

Contrarian angles: The market over-rotates to “Gen Z solves product-market fit”; historically (late-90s dot-com), novelty-driven teams produced high dispersion—expect 60–70% of early entrants to fail to scale. Mispricing exists in broad AI indexes that ignore execution risk; prefer concentrated bets where KPIs (12-month retention >80%, revenue-per-employee >$150k) are verifiable. Unintended consequence: wage inflation for juniors may compress margins in low-price-power segments, so cap exposure to pure labor-arbitrage models.

Key Decisions for Investors

• Establish a 1.5–2.5% long position in Colgate-Palmolive (CL) with a 6–12 month horizon to capture digital/Gen Z-driven e-commerce tailwinds; add a 3-month call spread (buy 1 5% ITM call, sell 1 15% OTM call) sized 0.5% notional if quarterly digital revenue growth >5% QoQ.
• Reduce exposure to Goldman Sachs (GS) by 1–2% of equity weight and implement a 3–6 month put spread (buy 1 7.5% OTM put, sell 1 15% OTM put) sized to the reduced position to hedge cultural/innovation lag risk; reassess after next two earnings calls or if GS announces concrete AI talent investments >$200M.
• Execute a pair trade: long CL (2% NAV) vs short GS (1.5% NAV) to express relative winners/losers over 3–12 months; target pair profit if CL outperforms GS by +15% or cut if spread narrows to -5% relative.
• Monitor regulatory catalysts: track SEC/FTC/European AI/privacy rule proposals and major ID-verification contract awards over the next 90 days; if proposed rules imply >10% revenue risk to identity/verification vendors, reduce AI/ID exposure by 50% within 10 trading days.