Building Talent Infrastructure for Economic Mobility

Mexico is often described as living through an “education crisis.” Too many students leave school early. Too many graduates struggle to find quality jobs. Too many employers complain they can’t find the skills they need.

But there’s a quieter, more destabilizing possibility: Mexico doesn’t just have a learning problem. It has a talent conversion problem. We’ve gotten better at producing schooling. We’ve been far less consistent at converting human capability into broad-based prosperity.

That’s why one detail in the World Bank’s "2025 Poverty and Equity Assessment for Mexico" lands like a clear call to action: Closing the gap in social security coverage could reduce extreme poverty more than marginal gains in education access because social protection changes when households can absorb shocks, stay healthy, keep children in school, and participate in the labor market.

In other words, the story is not that “education doesn’t matter.” It’s that education is being asked to do the job of an entire system.

The Uncomfortable Pattern: Diplomas Rise, Fragility Persists

Mexico’s educational attainment has improved over time. Yet, social outcomes remain volatile. Poverty moves, but not at the pace — or stability — you’d expect from expanding access to schooling.

This doesn’t mean Mexico is failing to “produce students.” It means Mexico is failing to compound the assets that turn learning into economic capability.

If you look at it through that lens, the “talent problem” stops looking like a pipeline issue (“more schooling”) and starts looking like a balance-sheet issue: Are we building, maintaining, and compounding the conditions that allow skills to become income, mobility, innovation, and dignity?

Because talent is not just something people have. Talent is something a society either enables or wastes. A country can be great at producing credentials — and mediocre at building capability

In practice, Mexico has often produced credentials without the complementary conditions that convert learning into productivity:

• stable health coverage (so learning and work have “uptime”)
• safe childcare (so families can plan and participate)
• reliable transportation (so opportunity is reachable)
• functional local labor markets (so skills have a place to land)
• credible pathways from school into decent work (so effort feels rational)

When those conditions are missing, the system leaks value before learning, during learning, and especially after learning — through informality, weak protection systems, care burdens, territorial productivity traps, and a fiscal architecture that often rewards yesterday over tomorrow.

So the sharper frame is: Mexico has a talent utilization crisis.

This is not an argument against education. It’s an argument against the fantasy that schooling alone can compensate for a labor market that:

• struggles to formalize
• under-rewards skills
• builds weak bridges from learning to quality employment

Social protection isn’t “welfare.” It’s talent infrastructure. Protection systems shape how people take risks, move jobs, invest in skills, and sustain employability through shocks.

A worker without health coverage or a pension isn’t just “less protected.” They’re structurally pushed into short-term decisions: informal jobs, unstable earnings, lower mobility, fewer realistic pathways for upskilling.

That’s why “talent infrastructure” needs a broader definition — a new operating system definition:

• Social protection = risk management for human capital.
• Health access = uptime guarantee for learning and work.
• Income stability conditions = the ability to plan long term (because most people are more worried about month-end than the end of the world)

When families are fragile, the future becomes expensive. Long-term learning becomes a luxury good. 

Mexico doesn’t need one plan. It needs a strategic portfolio. The strategic resource here is collective intelligence: the ability of a society to sense signals, interpret change, imagine alternatives, and coordinate action at scale.

Mexico should stop arguing about a single “master plan” or repeating “more education,” and start building a portfolio of strategic moves that performs across multiple plausible futures.

Two simplified scenarios make the contrast visible:

1. Current trajectory (slow improvement, weak conversion): Education access improves incrementally, but labor markets remain segmented, informality persists, productivity growth stays modest. People get diplomas, but the system under-converts learning into earnings and innovation. Social security gaps keep households fragile.
2. Unlock human capital (care + protection as economic policy): Mexico treats childcare and care infrastructure as core economic policy. Female participation rises, household incomes stabilize, child development improves, and skill investments finally have room to pay off. Social protection becomes a platform for labor mobility rather than a patchwork for welfare.

In that scenario, the barrier is not “women lack talent.” The barrier is that the system treats childcare and eldercare as personal logistics rather than national talent infrastructure.

And Then AI Shows Up and Flips the Table

Artificial intelligence isn’t just changing what people learn. It’s reshaping how they develop expertise, form professional identities, and cultivate the capacities that define human potential.

Generative AI promises personalization and efficiency. It also threatens to disrupt the very conditions through which people become capable:

• the struggle that builds mastery
• the friction that develops empathy
• the choices that forge agency
• the reflection that turns experience into wisdom

A strange inversion is underway. Technical skills that once defined career success are becoming more commoditized, while uniquely human capabilities — relationship building, strategic thinking, judgment, empathy, creativity — rise in value.

But here’s the catch: AI can eliminate the repetitive practice and controlled frustration that historically built expertise. And when AI intermediates human interaction, it can reduce exposure to the experiences that cultivate empathy and relational capability.

So this isn’t just a debate about “AI in classrooms.” It’s a debate about what kinds of humans a society is optimizing for.

Education Can't Remain 'Preparatory' in an Ever-Changing World

Historically, education has been treated as a phase preceding work: acquire knowledge → enter career → apply for decades. That model collapses when skills obsolescence accelerates and careers become non-linear. Lifelong learning shifts from personal virtue to economic necessity, from optional enhancement to survival requirement.

The most critical meta-skill becomes learning agility: the ability to grasp and apply new concepts quickly, transfer current capabilities into new contexts, and keep rebuilding value as conditions change.

And that brings us back to Mexico’s central challenge. 

The Real Wager: Make Learning Count

Mexico’s next leap won’t come from asking schools to do everything. It will come from aligning the ecosystem so that when people learn, their society actually lets that learning count — as mobility, as resilience, as productivity, as dignity. 

Because the future won’t reward the countries that produce the most diplomas. It will reward the countries that build the best conversion systems: the institutions, protections, pathways, and cultural norms that turn human potential into shared prosperity, even under shock.

When a Mexican student works hard and gets better, does the country have an operating system that can recognize it, reward it, and compound it?

That’s the real “education crisis.” And it’s also the most solvable kind because it’s not about talent. It’s about the strategic design of our talent infrastructure.