Beyond the AI Tool: What Higher Education Institutions Need to Get Right

Artificial intelligence is rapidly becoming part of higher education. Faculty are experimenting with generative AI in teaching, students are incorporating it into their academic work, and institutions are exploring opportunities across research, administration, student services, and academic program development.

But adopting AI tools is not the same as becoming an AI-ready institution.

The more important question for institutional leaders is no longer simply, “Which AI tools should we use?” It is how AI should support the academic mission, the people who deliver it, and the future direction of the institution.

From AI Experimentation to Institutional Strategy

In many higher education institutions, AI adoption begins from the ground up. Individual faculty members experiment with new approaches. Students discover new tools. Administrative teams identify opportunities to improve processes or increase efficiency.

This experimentation can be valuable. But disconnected adoption can also create inconsistent practices, uncertainty, duplication of effort, and institutional risk.

UNESCO has highlighted that institutional responses to AI need to move beyond guidelines alone and become embedded within broader strategies, competency development, governance, and long-term institutional planning.

The challenge, therefore, is not simply adopting AI. It is determining where AI creates meaningful value and how that value can be developed responsibly.

Five Areas Higher Education Institutions Should Consider

Preparing Faculty and Students for an AI-Enabled Future

Technology decisions are only one part of institutional readiness. Higher education institutions also need to consider the capabilities their people will require.

UNESCO's AI competency framework for teachers emphasizes areas including a human-centered mindset, AI ethics, AI foundations and applications, AI pedagogy, and the use of AI for professional learning.

Its student framework similarly emphasizes responsible engagement with AI, ethical understanding, foundational knowledge, and the ability to participate meaningfully in an increasingly AI-enabled society.

This has implications not only for faculty development, but also for curriculum design, graduate capabilities, assessment, academic programs, and institutional strategy.

AI Is Also Changing How We Think About Learning

The impact of AI extends beyond the use of individual tools. It is beginning to influence fundamental questions about how learning is designed and demonstrated.

The 2026 EDUCAUSE Horizon Report identifies AI as a significant force reshaping higher education teaching and learning, including assessment, instructional design, academic support, and student–faculty relationships.

For institutional leaders, this creates an important opportunity: rather than responding to AI only as a technology issue, institutions can use this moment to reconsider how teaching, learning, programs, and institutional practices should evolve.

The Opportunity Is Bigger Than the Technology

AI presents higher education with an opportunity that extends well beyond efficiency.

It creates a reason to reconsider how students learn, how faculty teach, how academic programs remain relevant, how institutional work is organized, and what capabilities institutions will need in the years ahead.

The institutions that navigate this transition effectively may not necessarily be those that adopt the most AI tools.

They are more likely to be those that make thoughtful choices about where AI creates value, how people are prepared to use it, and how innovation remains aligned with institutional purpose.