AI Isn’t Replacing Jobs—But AI Spending Might Be
By Dr. Claire Brady, EdD
“If that sounds familiar, it should. Higher ed has seen its own version of this cycle—investing heavily in technologies, platforms, and pilots before establishing a sustainable model or measurable ROI. The lesson here isn’t to avoid AI—it’s to implement it strategically and sustainably.”
In higher education, we’re no strangers to cycles of hype and hope—especially when it comes to technology. The latest narrative making headlines is that AI is replacing jobs. But as Gary N. Smith and Jeffrey Funk argue in Fast Company, it’s not AI itself that’s eliminating positions—it’s the spending on AI.
This distinction matters deeply for college leaders trying to make sense of the labor market our graduates are entering, and the fiscal realities our own institutions face.
The Spending Spiral
Let’s start with the basics: AI infrastructure is expensive. Amazon’s capital expenditures jumped from $54 billion in 2023 to $118 billion in 2025. Meta secured a $27 billion credit line for data centers. Oracle plans to borrow $25 billion annually for the foreseeable future.
These companies aren’t laying off workers because AI has “replaced” them—they’re cutting jobs to offset enormous capital investments. It’s not automation displacing employees; it’s financial overextension.
If that sounds familiar, it should. Higher ed has seen its own version of this cycle—investing heavily in technologies, platforms, and pilots before establishing a sustainable model or measurable ROI. The lesson here isn’t to avoid AI—it’s to implement it strategically and sustainably.
The Illusion of AI-Driven Efficiency
Smith and Funk cite an MIT Media Lab study showing that 95% of generative AI business pilots have failed. Another survey found 96% of organizations haven’t seen major gains in efficiency, innovation, or work quality.
If those are the numbers in corporate America—with full-time tech teams and big budgets—what does that say for campuses just beginning their AI journey?
It reinforces what I tell college presidents and student affairs leaders every week: pilot smarter, not harder. The goal isn’t to add more tools; it’s to align technology with mission, strategy, and human capacity. Without clarity, we risk replicating the same “AI slop” businesses are cleaning up—work that’s faster, not better.
The Real Human Cost
Perhaps the most troubling part of the article is the effect of these exaggerated narratives on young people. When students believe that “there’s no point in preparing for jobs,” we’ve failed them twice—first by allowing tech myths to dominate the conversation, and second by not providing AI literacy and critical thinking skills to see through them.
Higher ed has a responsibility here. We must prepare students not for a world without work, but for a world reshaped by work. AI fluency—understanding what these tools can and can’t do—is now a core career competency.
Lessons for Higher Ed Leaders
Audit before you invest. Know what AI tools already exist in your ecosystem and what problems you’re actually trying to solve.
Lead with purpose, not panic. Don’t buy into scarcity narratives—build capacity through education and empowerment.
Keep people at the center. AI should amplify human capability, not replace it.
Teach the myth. Help students understand the economic, ethical, and cultural forces shaping AI—not just the technology itself.
AI isn’t replacing jobs—but unchecked AI spending might reshape the workforce in ways that hurt both companies and colleges. The opportunity for higher ed is to lead differently: with discernment, transparency, and purpose-driven innovation.
Because in the race to build “super-intelligent” systems, our smartest move may be to invest in super-intelligent people.
