3 AI Workforce Gaps Higher Ed Must Close

Gerry Bayne: Welcome to EDUCAUSE Exchange, where we focus on a single topic from the higher ed IT community and hear insights, perspectives, best practices, and more. Earlier this year, EDUCAUSE published a report titled The Impact of AI on Work in Higher Education, examining how AI is already changing the way employees across colleges and universities do their jobs. We'll include a link to the piece in the show notes. The report points to a growing workforce challenge. AI use moving faster than policy, training and institutional strategy. Employees are experimenting with tools on their own, departments are responding unevenly, and AI literacy is becoming essential before many institutions have made real time for it. In recent conversations about AI and the higher education workforce, three themes have emerged. The first theme is that AI adoption is outpacing policy.

Jenay Robert: I frame this as an urgent issue for leaders, not just IT leaders, although certainly those are included, but leaders across the organization because we already know it, we see it in this research, we see it in other EDUCAUSE research, that there are many risks associated with using AI tools in higher education and using AI tools for work in higher ed is no exception to that rule. So there are data privacy risks, there are data security risks, there are higher level risks like perhaps damaging our critical thinking skills if tools are used incorrectly. And so without the appropriate guardrails in place to guide people to use AI tools appropriately and effectively, there could be some very serious implications and consequences to that. In almost any situation, I think really making sure that our governance is in place is going to be the first priority.

Jackie Bichsel: People are being left on their own to flounder and experiment with AI on their own. That means that employees are putting proprietary and institutional information into non-sanctioned unprotected AI tools. And employees are going to use AI whether they have permission or not and whether they have guidance or not. So it's up to institutional leaders to provide clear unified strategy, policy, training, and guidance on the use of AI.

Gerry Bayne: Another concern is that effective AI strategy requires shared ownership.

Jackie Bichsel: I think that a lot of institutions are still harboring the notion that IT and only IT should be in charge of facilitating AI use at their institution. And I think it has to be a collaboration. IT should not be doing this work in isolation. The work of AI requires buy-in from the workforce. And whenever you're dealing with conversations around workforce policies and practices, I think it would be remiss to leave out HR. And that I believe that I know other senior leaders need to be involved as well, but I think that IT HR partnership will be integral to any successful AI effort.

Jenay Robert: We're at a really interesting point right now in the development of AI tools at a high level, not just in higher education and not just in work in higher education. So thinking at that bird's eye view of how AI tools are developing, what we're starting to see now, and this was predicted three, four years ago, that we would eventually get to this point where the model development would sort of level out a little bit. We wouldn't be having these amazing new capabilities every other week from the model themselves, but that we would be exploring more how to apply those models in ways that are really interesting and creative and helpful and effective. And that's where we are now. I think we're really starting to see people thinking carefully and intentionally, starting with this design perspective. What is the problem that I am trying to solve?

And how might I use, if it's appropriate, this is part of the exploration, if it's appropriate, how might I use an AI tool to solve that problem? And so we don't have all the answers yet because first, the tools are still being developed for these very specific use cases. But this is where really collaborating across the institution is important, bubbling up those use cases and then work with experts not only related to those use cases, but related to that more general category of AI technology to match. So what's the problem, what's the solution and how do we put those together? And that really requires working across institutional silos.

Jackie Bichsel: This can't just arise from IT or HR or any one department. All of senior leadership needs to be on board with an overall AI strategy. AI is going to continue to be fragmented, risky, disconnected until we have enterprise platforms, we have policies and procedures, and we have training that's accessible for all employees.

Gerry Bayne: The third theme is that AI literacy trails everyday use in the workplace.

Jenay Robert: I think one of the quickest wins in terms of supporting people in that ground up experimentation is really focusing on AI literacy initiatives. We know how important governance is and how long it takes to set up governance policies, guidelines, workflows and so forth. But I think one of the earliest steps in that process should be supporting AI literacy. And this can look like a number of things. We reported on this in the research a little bit, but of course it's common in the discourse right now, people talking about how do we support AI literacy. There are programs from EDUCAUSE, from other professional associations that people can jump into. There's plenty of free training available on YouTube even. I think it starts with supporting that learning mindset and that growth mindset for people and saying, "Hey, if this is something you're going to experiment with, you should be also learning about what AI is and what the appropriate uses of AI are."

Jackie Bichsel: The training you have in place is going to shape whether employees perceive AI as a threat or whether it's a tool for better efficiency. We're not seeing a lot of replacement of people in higher ed because of AI, but that fear is out there. So we need to be communicating about AI strategy and how people's roles, how their functions are going to change due to AI. We need to take away the fear and the only way we're going to do that is through some firm guidance, firm strategy around AI.

Gerry Bayne: AI adoption is outpacing policy. AI strategy requires shared ownership and AI literacy trails everyday use in the workplace.