How AI Has Begun Changing University Roles, Responsibilities

Artificial intelligence is beginning to impact jobs and policies within universities as adoption of the technology grows, a new study finds.

More than half (56 percent) of those surveyed said they have new responsibilities related to AI strategy, according to Educause, a nonprofit focused on education and technology. Most of those experiencing the change are executives (69 percent), followed by managers and directors (66 percent), staff (46 percent), and faculty members (39 percent).

“Above and beyond the other risks [with AI], the risk to our workforce is they’re already overworked and now we’re asking them to do extra things,” said Jenay Robert, a senior Educause researcher. She cautioned against adding more responsibilities without changes in job titles or descriptions.

“It’s an important finding in terms of supporting the workforce,” she said. “Codify the role in people’s jobs so they know what to expect.”

Educause’s first “AI Landscape Study” focuses on the impact of the increasingly pervasive technology. The study polled 910 people who work at universities, surveying them in November and December.

Its findings delved into new topics: namely, how—or if—AI is shaking up faculty members’ jobs, both in the work they are doing and how they use the technology.

“When October, November was rolling around, there was a shift where AI wasn’t a brand-new hot topic, but people were settling in, having job roles dedicated to it,” Robert said.

Few of the respondents were aware of new jobs being created because of AI, with only 11 percent stating they knew of new job creation. New jobs that were created included chief AI officer, senior AI adviser, chief data scientist and AI program manager.

The survey also touched on AI policies, which have been discussed but often remain murky for academics. Nearly half of respondents were not happy with the AI policies their university had in place, with 48 percent stating those policies did not address ethical and effective decision-making. About 20 percent of respondents said their AI-related policies were somewhat or extremely restrictive, in some cases banning students or faculty from using AI tools.

Of the universities making AI policies, nearly half of institutions (43 percent) are working with a third party to develop AI strategy, while 30 percent are working with peer institutions or networks and 22 percent are working with professional associations.

The largest focus of the newly created or altered policies is on teaching and learning (95 percent). Academic integrity falls in that category, according to respondents, with 72 percent saying their academic integrity policies have been impacted by AI. Policies related to technology, cybersecurity and data privacy were also affected.

Only 11 percent of respondents said that no one at their institution is working on AI-related strategy, with 73 percent stating “some or most” departments are working on some sort of AI strategy.

Despite the work on policies, Robert said there needs to be more communication across the walls often created in academia.

“I think the take-home message is if folks are not sure they can use the technology or know the risks, to reach across the silos and talk to people in privacy, security and IT departments and see what already exists,” she said. “And as the use cases bubble up [from faculty and staff], it’ll help leaders figure out what new policies or guidelines need to be created.”

Most of the policymaking, according to the survey, is due to fears that students are using AI for “inappropriate” purposes, with 68 percent of respondents stating that as a concern.

There’s also a focus on preparing students for the workforce, with 64 percent of respondents calling that their biggest goal. Only 25 percent planned on using AI adoption for research purposes, and just 17 percent viewed AI adoption as a way to boost the institution’s reputation.

Despite the growing focus on AI, there is still a lack of formalized training at institutions: only 56 percent of universities train their faculty members in AI, with the numbers dipping for staff (49 percent) and students (39 percent). There’s also a lack of long-term focus and goals, according to the report, which found only 7 percent of institutions are working to establish AI-focused senior leadership positions and just 14 percent are budgeting for long-term AI costs.

Consistent with many other recent surveys, the Educause study also found that generally there is cautious optimism about AI among faculty, an acknowledgment that AI must to be taught to students and ever-present concerns about academic integrity.