Your Institution Is Investing in AI. Are You Investing in Your People?

by Claire L. Brady

A statistic from Deloitte recently stopped me in my tracks.

Organizations are investing heavily in artificial intelligence, but 93% of AI spending is going toward technology, infrastructure, and data. Just 7% is being invested in people-related capabilities.

The more I thought about it, the more it felt familiar.

Across higher ed, institutions are purchasing licenses, developing AI policies, launching pilot programs, experimenting with chatbots, exploring agentic AI, and building governance structures. These are important steps. In many cases, they are necessary steps.

But I often find myself asking a different question: Are we investing in our people at the same rate we are investing in our platforms? Because technology adoption and human adoption are not the same thing.

An institution can purchase an enterprise license in a matter of weeks. Building confidence, competence, and capacity across an organization takes far longer.

Yet that is where the real work lives.

Over the past three years, I have had the opportunity to work with hundreds of higher education leaders, boards, associations, faculty members, and staff as they navigate AI adoption. What I consistently observe is that the institutions making the greatest progress are not necessarily the ones with the largest budgets or the most sophisticated tools.

They are the ones investing in their people.

They are helping faculty understand how AI may impact teaching and learning. They are giving staff permission to experiment and learn. They are equipping leaders to think strategically about implementation rather than reactively about risk. They are creating space for conversations about ethics, transparency, student success, accessibility, and institutional values.

In other words, they are treating AI as a people strategy, not just a technology strategy.

That distinction matters.

One of the biggest misconceptions about AI is that implementation is primarily a technical challenge. In reality, the technology is often the easiest part. The harder work involves changing habits, building trust, developing new skills, redesigning workflows, and helping people understand how AI fits into their daily work.

A new platform does not automatically create transformation.

People do.

Five Ways Higher Education Leaders Can Invest in People, Not Just Platforms

If AI is truly a human transformation challenge, then our investments should reflect that reality.

1. Build AI Literacy Across the Institution—Not Just the IT Division

AI literacy is no longer a technical competency. It is a leadership, teaching, learning, and workforce competency.

Every employee should understand the opportunities, risks, limitations, and responsible uses of AI within their role. That means providing learning opportunities for faculty, staff, administrators, and student employees—not assuming a small group of experts will carry the work.

2. Equip Managers and Supervisors to Lead Through Change

Many supervisors are being asked to implement AI initiatives without receiving guidance on how to lead conversations about them. Invest in department chairs, directors, deans, managers, and supervisors. Help them understand how AI may reshape workflows, expectations, and team dynamics. The success of your AI strategy will often be determined by the people closest to day-to-day operations.

3. Create Safe Spaces for Experimentation

People rarely build confidence through policy documents alone. Give employees opportunities to explore AI tools, share successes, discuss concerns, and learn from one another. Encourage thoughtful experimentation and normalize the fact that learning often involves uncertainty. The goal is not perfection. The goal is capability.

4. Develop a Shared Institutional Framework

One of the biggest barriers to AI adoption is that different groups are often having different conversations. Faculty are discussing academic integrity. Student affairs professionals are discussing student support. Marketing teams are discussing content creation. Leadership teams are discussing risk and governance. Create opportunities for these groups to learn together. A common read, shared professional development experience, campus AI summit, or cross-functional task force can help establish a common language and shared understanding.

5. Measure Readiness, Not Just Usage

It is easy to track licenses, logins, and tool adoption. It’s harder—but more important—to assess confidence, competence, and preparedness.

Ask questions such as:

• Do employees understand when and how to use AI responsibly?

• Do supervisors feel equipped to lead AI-related change?

• Do faculty feel confident discussing AI with students?

• Do staff understand how AI supports institutional priorities?

Usage tells you whether people have access. Readiness tells you whether they are prepared.

Creating a Common Language

One practical approach I often recommend is creating a shared language around AI across the institution. Too often, faculty, staff, administrators, and students are having separate conversations about AI. A shared learning experience can help bridge those gaps and create a foundation for more productive dialogue.

That is one of the reasons I wrote “AI with Intention”. Increasingly, institutions are using the book as a common read for cabinet teams, AI task forces, faculty groups, leadership development programs, and campus committees. Not because it has all the answers, but because it helps create a shared framework for asking better questions about AI adoption, governance, culture, and strategy.

The goal is not simply to increase AI usage.

The goal is to increase AI readiness.

Those are not the same thing.

As higher ed continues to navigate one of the most significant technological shifts of our time, leaders should remember that successful AI adoption will not be determined solely by the quality of the tools they purchase. It will be determined by the confidence, capability, and preparedness of the people using them.

Technology matters. But people remain the greatest investment an institution can make.

The colleges and universities that thrive in the years ahead will understand that AI transformation is not primarily about platforms.

It is about people.

Note: this image was created using ChatGPT