AI is Growing Up
By Dr. Claire Brady
The AI “wow” phase may finally be giving way to the “how” phase.
According to Gartner’s latest report, more than half of IT infrastructure and operations leaders are now using AI to cut costs—but not through splashy chatbots or futuristic, student-facing tools. Instead, they’re focusing on the unglamorous but essential work of automation: optimizing cloud spending, streamlining infrastructure, and improving operational efficiency. In Gartner’s words, “frumpy but functional” is back.
And that’s good news. It signals a maturing relationship with AI—one that’s moving beyond the hype cycle toward measurable, mission-aligned outcomes. For the past two years, many colleges and universities have been swept up in the race to “adopt AI.” We’ve seen hundreds of pilots launched, task forces formed, and tools tested. Some have succeeded; many have quietly faded. But the institutions that are seeing real value are often the ones using AI not as a headline, but as a lever for operational improvement.
Higher education’s version of this “sobering-up” looks like a shift from experimentation to integration. Instead of asking “What’s the coolest AI tool we can try?” forward-thinking leaders are asking “Where can AI reduce friction, create capacity, or enhance decision-making?”
Think about automating transcript evaluations, simplifying purchasing workflows, managing facilities data, or monitoring student systems more intelligently. These aren’t the kinds of projects that get presidents invited to national panels—but they’re the ones that free up staff time, reduce costs, and create space for the deeply human work that defines our institutions: mentoring students, building community, and fostering belonging.
Gartner’s findings also come with a familiar warning: 50% of leaders cited budget constraints as their biggest barrier to adoption, and even fewer reported having the safety, governance, and transparency structures needed to sustain AI responsibly. That tension—between opportunity and restraint—is one that higher ed knows all too well.
Budgets are tight. Staff are stretched. Leaders are under pressure to deliver both innovation and accountability. But perhaps that’s why this moment matters so much. A more pragmatic approach to AI—one grounded in mission, ethics, and measurable impact—can actually help higher ed institutions model what responsible AI leadership looks like.
Maybe what’s emerging isn’t disillusionment at all, but maturity. A recognition that transformation doesn’t always announce itself with fanfare. Sometimes it’s found in the quiet efficiency of an automated workflow or the relief of a registrar who just gained an hour back in her day.
The great AI sobering-up isn’t a buzzkill. It’s a reset—an invitation to focus on what works, start small, and scale what matters. For colleges and universities, it’s a reminder that sustainable innovation doesn’t have to be loud to be transformational.
In the end, this might just be the version of AI progress higher ed needs most: not a revolution powered by hype, but a steady evolution powered by purpose.
Read the full Gartner report: https://www.gartner.com/en/newsroom/press-releases/2025-10-29-gartner-survey-54-percent-of-infrastructure-and-operations-leaders-are-adopting-artificial-intelligence-to-cut-costs
