The rapid rise of artificial intelligence has created a dual imperative for leaders: build the technology and build the workforce capable of using it wisely. As AI becomes embedded across industries—from healthcare and automotive to education and public policy—the question is no longer whether people will use AI tools, but how well they will do so, and to what end.
The panelists at CES 2026—leaders from Amazon Web Services, Oshkosh Corporation, Teach Access, and the Consumer Technology Association—converged on a core message: technical skills matter, but they are insufficient on their own. The next generation of tech talent will be defined as much by curiosity, empathy, and critical thinking as by coding or prompt engineering.
For executives and educators, that shift demands a broader view of “AI readiness”—one that spans the full lifecycle from K–12 to higher education, apprenticeships, and ongoing workforce development.
Organizations like AWS are investing heavily to scale foundational AI skills. Amazon, for instance, has already met its goal of training 29 million people in cloud skills ahead of schedule and has now committed $2.5 billion to train 50 million people in AI by the end of the decade. But the panel was clear: technical fluency is only one side of the equation.
Three categories of skills emerged as essential:
Panelists warned against treating AI as a universal solution. Tools remain fallible and require human oversight. Students and workers must:
In short, the emerging “AI professional” is not a passive user, but an active editor, evaluator, and designer of AI-enabled systems.
A recurring challenge is speed: technology advances faster than curricula, accreditation processes, and institutional governance. Yet the panel’s examples suggest that this gap is manageable when industry and education collaborate deeply and continuously.
Several practical models stood out:
These experiences share common design principles that leaders can replicate:
When education systems move slowly, agile partnerships—with clear goals, time-bound programs, and tangible outputs—can keep students aligned with the technological frontier.
Panelists repeatedly emphasized that companies cannot simply complain about skill shortages; they must help solve them. The most effective organizations are treating talent development as a long-term, community-wide investment rather than a narrow recruiting tactic.
Examples ranged from large-scale online programs to deeply local engagement:
Importantly, these efforts are not viewed as proprietary advantages. As one panelist noted, the goal is not to guard programs as competitive secrets, but to encourage more companies to do the same in their communities.
For senior leaders, this suggests several actionable commitments:
The most meaningful signal to students and teachers is not a press release, but the visible presence of industry professionals who show up, share their work, and stay engaged over time.
AI literacy is increasingly a public policy priority. Initiatives such as the White House’s Pledge to America’s Workers and related AI literacy pledges illustrate how governments and companies can align around shared targets—like reaching millions of learners and thousands of educators with AI training.
Yet the panel underscored two often-overlooked dimensions of this policy–technology intersection:
For executives, that means engaging in policy conversations early and constructively—advocating both for responsible guardrails and for the flexibility innovators need. It also means embedding accessibility and inclusion into every AI initiative, from data collection to interface design, rather than retrofitting compliance at the end.
Educators sit at the center of this transformation, but they are often under-resourced, overextended, and asked to prepare students for jobs that do not yet exist. While that tension is not new—past generations grappled with computers, mobile phones, and the internet—the scale and speed of AI heighten the stakes.
The panel highlighted a few concrete ways organizations can support teachers more effectively:
Equally important is recognition: many teachers invest unpaid hours in extracurricular STEM programs. When companies “show up”—not just with checks, but with time, tools, and ongoing collaboration—they send a powerful signal to both educators and students that this work matters.
If business, government, and education get this right, the next generation of tech talent will not simply be expert users of AI. They will be:
No single institution can create this future alone. But leaders across sectors can start now by broadening their definition of “AI skills,” expanding their partnerships with educators, and treating curiosity and humanity—not just code—as core competencies. The innovators of tomorrow will be shaped by the choices organizations make today about how, and with whom, they build the AI-ready workforce.