The AI talent challenge is not a shortage problem. It is a strategy problem. Nearly half of IT decision-makers ranked generative AI tools as their top budget priority for 2025, according to the AWS Generative AI Adoption Index. Yet most admit they have no clear strategy for recruiting, reskilling, or upskilling workers for AI. This gap between technology investment and workforce readiness is not just creating competitive risk, but it is widening by the day. The solution requires no new infrastructure, only strategic partnerships that can develop and scale talent pipelines at the speed business demands.

Many companies are investing heavily in AI tools while simultaneously figuring out the human capabilities and learning infrastructure required to scale effectively. Even the most experienced HR leaders tell us they are unsure where to begin.

However, this instability also presents tremendous opportunities for experimentation. Talent leaders can still serve as the key conduit to supercharge their company’s productivity without knowing all the answers. That is because they have access to a valuable but often underused partner: higher education.

Higher education remains one of the most underutilized assets in corporate AI talent strategy. Community colleges, independent colleges, public universities, and research institutions have the reach, governance, and instructional expertise to translate industry needs into workforce-ready programs. And they are ready to move at the speed business requires during this unique time.

Here are three ways companies can get ahead of the AI wave by partnering with higher education leaders.

1. Co-define the AI skills that matter most.

Executives have the clearest view of how AI is reshaping their firm’s work. They know which tasks are being automated, which roles are being augmented, and which new capabilities are emerging. The companies moving fastest are identifying the highest priority roles, gathering learnings on how employees are using or not using AI in those roles, and then codifying those findings to develop and upskill talent through higher education.

Having a shared language is critical. The Business-Higher Education Forum recently developed an employer-validated framework through interviews with more than 100 corporate and education leaders that identifies seven essential competencies: critical thinking, ethical and responsible AI use, data literacy, continuous learning, communication, technical fluency, and digital and computational skills. Most of these are durable human skills, not technical ones like coding.

When a Fortune 500 financial services company mapped these competencies to their customer service roles, they discovered employees needed AI collaboration skills more than technical training: the ability to work alongside AI to personalize customer interactions, not just operate the tools. Ultimately, it will be a blend of durable human capabilities, evolving technical skills, and the learner’s career stage that determines whether AI becomes a productivity enhancer or an underused investment.

2. Use higher education as a safe, scalable environment for AI experimentation.

AI skills integration requires safe environments where teams can test ideas, learn quickly, fail safely, and build confidence. Higher education institutions are positioned well to provide exactly that.

The University of Sheffield in the UK is leveraging the Innovation Sandbox on AWS to implement generative AI training for law students. The sandbox enables cloud administrators to automate the management of temporary environments with built-in service control policies, spend controls, and account recycling mechanisms. Sheffield law students are building an innovative Law Advice clinic agent using Amazon Bedrock, gaining hands-on experience with frontier AI tools in a governed, cost-contained environment.

Miami Dade College takes a different approach. Through its multi-company AI Center, the college upskills working professionals using applied AI skills delivered through actual workplace tools and simulated labs. More than 60% of participants are over age 26, and companies gain access to talent already familiar with their industry context while sharing program development costs.

These collaborations offer companies a low-risk way to accelerate learning without creating new internal cost centers or significant compliance risks.

3. Build lifelong learning pathways now or risk falling behind later.

Companies that treat AI upskilling as a one-time training effort will find themselves perpetually behind. The difference comes from aggregated industry input: instead of each company educating institutions individually, they contribute to shared frameworks that multiple universities implement simultaneously.

BHEF’s AI & Future of Talent Collaborative brings together leaders across industry and higher education to surface common challenges, identify critical gaps, and inform the design of new solutions to keep companies competitive and prepare learners to thrive in an AI-enabled workplace. AWS Skills to Jobs Tech Alliance is a global coalition of higher education institutions, nonprofit collaborators, government entities, and businesses that addresses the skills gap and prepares learners for in-demand tech jobs. Together, these initiatives create a “no wrong doors” approach with regional higher education partners. Investment in one partnership benefits from curriculum updates driven by broader industry signals, helping leaders work with institutions that more intimately understand the context of their industry, supply chain, or firm.

Executed well, these shared bodies reduce implementation costs and increase the speed at which talent strategies adapt, giving both companies and educators a reliable foundation for ongoing AI-enabled workforce development.

Getting Ahead

AI will reshape every business, but not equally. Organizations that co-design skill expectations, leverage higher education as an experimentation ground, and build lifelong learning pathways will move ahead faster. Those who wait will see the gap widen quickly.

The fastest road to an AI-enabled workforce is a shared one. Now is the moment for corporate leaders to treat higher education not as a distant supplier, but as a core partner in building the workforce that the AI era demands.

Kristen Fox is CEO of the Business-Higher Education Forum. Valerie Singer is general manager of global education at AWS.