Results from a New EDUCAUSE Landscape Study

Conducting a landscape study is challenging when the landscape is changing as quickly as artificial intelligence has been in the last two years, says Jenay Robert, Senior Researcher at EDUCAUSE.

“But toward the end of last year, we saw that the initial hype and panic from generative AI was starting to chill a little bit,” she notes. “So we wanted to capture that sweet spot where enough time had passed but not so much that we were losing the momentum to figure out what was important to the community.”

The result is the inaugural 2024 EDUCAUSE AI Landscape Study exploring sentiments and experiences with AI in higher education using surveys distributed to educators in late 2023. The report has findings on the areas of:

• Strategic planning and readiness
• Strategic leaders and partners
• Policies and procedures
• Workforce and the future of AI in higher education.

Overall, the results show that within most institutions at least some people are moving fast to incorporate AI into teaching and learning or other operations, but institutions struggle to make that work comprehensive, coordinated and strategic.

After the survey findings, the report outlines appropriate and inappropriate uses of AI and the opportunities and risks to colleges and universities planning for AI.

Getting a grip on planning for AI

One key finding from the study showed most institutions are working on AI-related strategy. Of the respondents, only 11 percent said no one was working on an AI strategy at their institution.

“The community really understands this is the new world,” Robert says. “We have a responsibility to prepare our students to be responsible citizens and workers and humans in that world.”

The report shows how challenged colleges and universities are to keep up. “By the time you’ve assembled six committees to decide how you want to use AI and then another committee to review the results of those six committees, it’s just too late,” Robert says. “AI has already proliferated, and it’s all over the campus.”

That puts a big burden on institutions to be forward looking. “You have to be able to kind of see around the corner, to some extent,” Robert says. “Not to predict the future, but to think about how what’s happening today will impact the next 10 years and to work toward the future you want to see, as opposed to reacting to things as they come.”

Clarifying what AI is

Concerns about academic misconduct and other inappropriate uses of the technology were among the first reactions for many faculty. For instance, the study found a majority of respondents (78 percent) felt AI had impacted academic integrity.

Robert says a helpful distinction for educators concerned about plagiarism is between generative AI and general AI. Generative AI helps users create new content like images, videos, and documents, whereas general AI has the potential to execute complex tasks or processes.

“I think part of those responses [about academic integrity] were because of that conflation, where people are much more worried about generative AI,” Robert says. “If they dig deeper, some of those other AI functions would not be as troublesome for them.”

Making AI planning equity centered

Robert says she was happy to observe in the survey responses a consistent concern with student success, even if “the community was concerned about the proliferation of AI. It was great to see we were maintaining our focus on students and what students need at the end of the day.”

Put another way, the motivations for working on AI may be reactive — i.e. “keeping up” — but the goals were often more aspirational. For example, more than 60 percent of respondents said their goals for strategic planning for AI were preparing students for the workforce or exploring new methods of teaching and learning.

Robert says equity, inclusion, and accessibility came up a lot in open-ended responses. Bias in the development of AI “is a really hard problem we haven’t been able to solve in even simpler technologies,” she says.

“We have to be realistic, but we have to maintain that steadfast focus on minimizing and reducing bias. There’s no on-off switch for equity. There are going to be elements that are more or less equitable. So I would love for people to understand and be comfortable with that nuance.”

Related reading — Principles for Understanding AI in the Classroom

Moving from reaction to action

Robert hopes the landscape study equips readers to be more proactive about the emerging AI technology to minimize troubles later. One area where that can happen is in security and privacy.

“When any random person at your institution doesn’t know about the privacy and security policies related to AI, for example, that could have huge implications,” she says.

She says a lack of awareness around standards and policies is a symptom of a larger issue: siloing. Operating in isolation within or across institutions keeps educators in a reactive state as new AI tools roll out.

Ultimately, educators are restricted in their ability to effectively, ethically, and equitably use technologies by being forced to play catch up.

“We struggle with practices being fast enough to keep up with what’s going on in the world,” Robert says. “What you and I talk about this week will be outdated next week.”

Robert encourages faculty to play with new AI tools that interest them and talk to others about what they might be using. Communication and collaboration can improve security and privacy as educators surface their needs and use cases to the appropriate teams and find timely solutions. Effective communication and collaboration also positions institutions to develop a solid framework for their AI policy.

The report concludes with reference to several practical resources, including EDUCAUSE’s 2024 Action Plan: AI Policies and Guidelines, and EDUCAUSE’s 2023 Horizon Report Action Plan: Generative AI, which outlines goals and action steps on how generative AI can be incorporated into higher ed in an ethical and equitable way.