Open vs. Closed AI: Strategic Choices That Will Shape Higher Education

Higher education’s next breakthrough won’t come from proprietary platforms alone. It will come from collaboration—and from intentional choices about the technology ecosystems we build and support.

As the AI market reaches an inflection point, large enterprise solutions such as Google Gemini are becoming increasingly closed, limiting institutions’ ability to experiment, customize, and rapidly innovate. At the same time, a growing set of open platforms—from Meta and others—are accelerating possibilities for co-creation, interoperability, and shared value. Higher education now faces a strategic choice: which direction will enable the greatest long-term impact, and what does it mean for access, equity, and institutional resilience?

Across the sector, open source is emerging not just as a technical preference but as a strategic imperative, fueling scalable systems that serve hundreds of thousands of students, enable new pathways like apprenticeships, and deliver measurable cost savings while expanding access. Yet the question remains: is openness inherently better—or simply better suited to the outcomes higher education seeks?