Before accepting outside capital, university leaders and boards should define the purpose of the investment.
That switch was survivable for a decade because activity and revenue moved in tandem. AI just broke the correlation, and that is why the contradiction suddenly has a price.
Few have figured out how to make change tangible, how to show every person in the organization what is different and why it matters to their day.
After all, nobody ever lost their job because they invested in the unanimously determined next big thing.
Security teams have made real progress securing the software supply chain, but traditional trust signals do not prove code is safe to run.
AI activity is visible and easy to report, but progress is harder to define and even harder to measure.
Getting buy-in from the executive team on AI adoption can often be the easy part.
Accuracy creates confidence in the records. Business-ready data creates confidence in the decisions.
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AI is moving beyond efficiency toward better decision-making. Here’s how leaders can use context, continuous learning and outcomes to turn AI into a strategic advantage.