Higher education IT leaders are bullish on artificial intelligence (AI) but struggle to scale pilot projects organization-wide, according to new research from MeriTalk.
Nearly all leaders say “getting AI right is essential to students’ success” (97%), and 91% report productivity gains from generative AI. Two-thirds (65%) already include some form of AI education in the curriculum, and 79% are actively exploring agentic AI, according to the research, “Sandbox to Scale: The people, processes, and platforms needed to accelerate AI in higher education,” which was underwritten by Dell Technologies and NVIDIA.
Early wins are tangible and span both academic and operational domains, the research found. The most successful AI pilots to date center on research acceleration and discovery (43%), academic advising (43%), personalized learning and tutoring (40%), and facilities management (40%).
These pilots hint at a future where institutions deliver more tailored services and speed scientific breakthroughs – if institutions can translate those proofs of concept into scaled capabilities.
Yet just 12% of higher education IT leaders say they have scaled AI across multiple workflows organization-wide, and a striking 87% say they’re more likely to launch a new pilot than expand an existing one. That pilot-heavy posture reflects real headwinds: The top reasons projects stall include poor data quality or availability, insufficient cybersecurity planning, and difficulty integrating with existing systems.
To push past the pilot phase and successfully scale AI, the study points to the three Ps: people, processes, and platforms.
On the people front, the most impactful steps include empowering informal AI advocates and improving change management practices – a recognition that culture and communications can be as decisive as code.
In the process arena, leaders highlight building quality data pipelines and establishing sandbox environments for safe, iterative testing. And on platforms, expanding compute and storage capabilities alongside adopting scalable cloud or hybrid environments are the moves most likely to accelerate institutional rollout.
Governance and infrastructure loom large. Asked about the No. 1 factor in AI success over the next five years, IT leaders chose scalable, secure infrastructure, followed by actionable governance and an AI-fluent workforce.
The research explores:
- Top AI priorities for higher education IT teams
- Greatest opportunities for AI to impact higher education experiences and outcomes
- The steps institutions are taking to successfully scale pilot projects campus-wide
For more insights, download the research: “From Sandbox to Scale: The people, processes, and platforms needed to accelerate AI in higher education.”