The results are still unproven.
From data architecture to post-launch ownership, this report reveals what it takes to run AI in a sector constrained by shrinking budgets and thinner teams.
Believe AI is making their institution more competitive.
Say their AI initiatives haven’t met expectations.
How to Use the Report
Benchmark Your Program
See where your institution sits against 75 peers. The appetite to expand is already here: 71% say scaling what works is their top priority for the year ahead, yet only 11% strongly agree AI has delivered measurable value so far.
Spot the Patterns
Data is the hardest part of launching AI, and it doesn’t get any easier after go-live. 80% of institutions keep hitting data accuracy and availability problems once the technology is running.
Apply the Findings
Get the practices that keep AI delivering after launch. Learn how institutions build the data foundation, governance, adoption, and measurement frameworks that turn AI into lasting business value.
Resource the Work
Running AI is its own job. The resource shortages that make AI appealing are the same ones that make it hard to run, and 59% of institutions name internal bandwidth as a top constraint.
Senior Higher Education Leader, 2026 AI Operations Survey
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Senior Director, Innovation & Emerging Technology
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VP, Education
Build AI That Makes An Impact
See why AI investment keeps outpacing returns across 75 higher education organizations — and the right moves to close the gap.