On 20 May 2025, the Oxford Martin School welcomed Dr Pablo Egaña-delSol, Visiting Fellow in the Future of Work programme, to present his latest research on how the Fourth Industrial Revolution—and Generative AI in particular—is transforming labour markets in developing economies. Over a 45‑minute seminar followed by audience Q&A, Dr Egaña-delSol summarized cross‑regional evidence, highlighted rising inequalities, and proposed strategic reskilling pathways.

The Automation & AI Exposure Gap

• Higher Automation Risk: Drawing on Frey & Osborne indices, Dr Egaña-delSol showed that workers in emerging economies face up to 2.5× greater automation risk than their OECD peers—nearly 60 percent of jobs are “high‑risk,” versus under 25 percent in wealthier nations.
• AI Exposure vs. Automation: Using both patent‑based AI exposure scores and traditional automation metrics, he demonstrated that AI threatens not only routine and low‑skill roles but increasingly high‑skill cognitive tasks (e.g. teaching, finance, research), upending the historical “education as protection” pattern.

Uneven Labour‑Market Impacts

• Gender Disparities: Unlike in the OECD, where blue‑collar men were hardest hit, in many Latin American and African economies women face higher automation and pandemic‑recovery shortfalls, exacerbating pre‑existing gender gaps.
• Employment Polarization: AI‑exposed occupations saw faster growth at both the highest‑ and lowest‑paid ends of the wage scale—while mid‑wage roles stagnated—mirroring a “J‑curve” of widening inequality.
• Stagnant Wages: Across eight Latin American countries, higher AI‑exposure did not translate into wage growth, underscoring the need for proactive upskilling rather than relying on market‑driven skill premiums.

Strategic Reskilling: The Chilean Talento Initiative

Dr Egaña-delSol evaluated Talento Digital, a Chilean public–private “boot‑camp” programme (400–480 hours over 5–6 months) designed to reskill and upskill 16,000 workers in digital fields:

• Upskilling Impact (Digital Natives → Advanced Roles): Significant earnings gains among participants from technology, design, and business backgrounds—up to a 20 percent increase in annual wages.
• Reskilling Limits (Non‑Digital Backgrounds → Tech): Participants from humanities or healthcare saw no significant benefit, highlighting that intensive short‑term training alone cannot bridge deep skill divides.

Policy Roadmap for Inclusive AI Transitions

1. Social Dialogue & Flexibility: Forge ongoing collaboration among unions, employers, educators, and government to rapidly adapt curricula and labour protections.
2. Education Reform: Embed critical thinking, creativity, and meta‑skills (e.g. adaptability, digital literacy) across primary–tertiary learning pathways.
3. Adaptive Social Safety Nets: Decouple benefits from formal contracts to support gig‑, platform‑, and informal‑sector workers facing AI‑driven churn.
4. Real‑Time Labour‑Market Intelligence: Deploy continuous forecasting and skills‑demand analytics to guide targeted reskilling investments.

Dr Egaña-delSol concluded that developing economies must move beyond passive AI adoption, leveraging strategic reskilling and institutional innovation to mitigate displacement risks and seize productivity gains. A recording of the seminar and slides will be made available via the Oxford Martin School website.

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