Education in the Age of AI

EVOLVE 2026 · MIAMI · MAIN STAGE · SESSION 04

The launch of the Frontier Institute of Technology and a panel of education and philanthropy leaders explored why the biggest constraint on AI may no longer be technology—but talent.

EVOLVE is Sand’s annual summit bringing together technology leaders, policymakers and practitioners working at the intersection of AI and critical infrastructure.

The conversation around AI often centres on models, compute and infrastructure. This session argued that the real bottleneck may be something far more human: talent.

Combining the launch of the Frontier Institute of Technology with a candid discussion among leaders in education and philanthropy, the session explored a growing challenge facing governments, employers and universities alike: how do you prepare people for an economy that is changing faster than education can keep up?

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THE 60-SECOND READ

Education is economic infrastructure, and it is out of sync with the economy it feeds. Curricula update every 4 to 8 years. Skills change every 12 to 24 months. The session’s verdict, across a university launch and a blunt leaders panel: America does not have a talent strategy at scale, and talent, not technology, is the constraint.

What This Conversation Revealed

1. The talent gap is becoming AI's biggest bottleneck.

The panel argued that organizations increasingly face a shortage of people prepared to work with AI—not a shortage of AI itself. As adoption accelerates, workforce readiness is becoming a competitive advantage.

2. Education must evolve as quickly as technology.

Traditional education systems were designed for a world where knowledge changed gradually. Today's economy demands a different model—one where learning is continuous, curricula evolve alongside industry and graduates leave with relevant, applied experience.

3. Preparing people is a shared responsibility.

Universities cannot solve the challenge alone. Employers, governments and educators all have a role to play, from redesigning hiring practices around skills to creating more opportunities for work-based learning and lifelong education.

Key Highlights

The current model is under pressure. The United States carries an estimated $1.77 trillion in student debt while 52% of graduates remain underemployed one year after completing college—raising questions about both affordability and outcomes.
The skills gap is widening. Only one in ten workers has received AI-specific training, while just 11% of business leaders believe today's graduates possess the skills employers need.
The opportunity is enormous—but so is the challenge. AI and automation could displace 92 million jobs while creating 170 million new ones by 2030. Meeting projected global demand would require the equivalent of 57,000 new university seats every day through 2035.
History offers a useful comparison. Don Gips reflected on previous moments of national transformation, arguing that just as the Sputnik era reshaped investment in education, AI demands a comparable rethink of how talent is developed.
A new model was introduced. The Frontier Institute of Technology launched at Evolve with AI integrated across every discipline, accelerated three-year degrees, industry-informed curricula, real-world projects and a flat tuition of $200 per month.

By the Numbers

$ 0 T

US student debt

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underemployed a year after graduating

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skills cycle vs 4-8 yr curricula

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Frontier flat tuition

In their words

“Progress happens at the speed and pace of trust.”

Leslie Gill, President & CEO, Rung for Women

Why it Matters

For much of the AI conversation, the focus has been on what the technology can do. This session shifted the question to something more fundamental: who will have the skills to use it?

The discussion highlighted a widening disconnect between education and the economy. Employers struggle to define the skills they need because AI is changing work so quickly. Universities struggle to update programmes at the pace industry demands. Workers, meanwhile, are expected to continually adapt, often without access to meaningful retraining. The result is a talent infrastructure that is increasingly out of step with the future of work.

Seen in that context, the launch of the Frontier Institute of Technology represented more than a new educational institution. It reflected a broader argument: that preparing people for the AI era will require new models of learning built around continuous adaptation, closer collaboration with industry and practical experience—not simply incremental updates to existing systems.

The conversation also challenged employers to rethink their own role. Rather than relying on credentials as proxies for capability, organizations will increasingly need to hire for skills, invest in lifelong learning and create clearer pathways for people to grow alongside AI.

Perhaps the session’s biggest insight was this: every discussion about the future of AI is ultimately a discussion about people. The organizations and societies that thrive won’t simply be those that build the best technology—they’ll be those that build the talent capable of turning that technology into lasting impact.