Why One Professor Abandoned the AI Resistance

Two years ago, Scott Latham, a business professor at the University of Massachusetts at Lowell, was one of academia’s leading voices of the resistance to artificial intelligence.

“AI is not your friend,” he wrote in a June 2024 editorial for Inside Higher Ed, imploring faculty to “pump the brakes on artificial intelligence in higher education,” lest robots take their jobs in the not-so-distant future.

But as the technology has evolved, so has Latham’s view on it. “For everyone who works in higher education, there is a great deal of pain and disruption to come,” he wrote in an editorial for The Chronicle of Higher Education in April 2025. “We can minimize the damage, though, by helping people understand how AI will transform higher education.”

Scott Latham/ UMass Lowell

Now, he’s not only embraced AI in his own classroom, he’s also trying to create a clearer portrait of how universities across the country are using it.

Last month, he and his colleagues, in partnership with the nonprofit Alliance for Data Science and AI, launched the AI Campus Index, an independent national ranking system that measures how well colleges and universities use and provide AI for their students, faculty and operations. According to the project’s website, its goal is “to help students, families, institutional leaders, and policymakers understand which colleges are truly embracing AI—not as a research novelty, but as a practical tool that improves student outcomes, faculty effectiveness, and campus operations.”

Latham told Inside Higher Ed that he hopes the index—which isn’t affiliated with any company or university—will serve as a “clearinghouse of higher education and AI” and a consumer transparency tool.

“We’re trying to cut through the AI noise,” he said. “We want to offer a sober perspective on how this technology is extending its footprint into the academy.”

Inside Higher Ed recently interviewed Latham about how he evolved from AI resister to adopter and the person leading the charge on measuring AI readiness.

This interview has been edited for length and clarity.

Q: What was your first reaction to the mainstream introduction of generative AI in late 2022?

A: My initial thoughts were that it was going to put me out of a job and that it was not going to be beneficial to the student in the classroom. Those concerns came from within the context of where AI was relative to its capabilities. It was a parrot on steroids.

It reminded me of when I was the age of some of my students. I would use CliffsNotes, which also circumvents the learning process. When a professor says to read The Great Gatsby and CliffsNotes tells me what it’s about in 10 pages, there’s no learning going on there.

I was very, very concerned about AI allowing that to happen on a much larger scale. At the faculty level, AI was kind of subverting my mission. And at the student level, it was preventing them from really engaging with what I was trying to do.

Q: You have since embraced AI as a teaching and learning tool. What changed?

A: I saw AI’s capabilities evolve at a pace that I hadn’t even imagined, and I saw the predicament of higher education worsened largely because of the incoming Trump administration. Those two things caused me to shift my perspective on AI from a threat to an opportunity to help higher ed evolve into something that will endure.

It is manifesting itself incredibly differently on every campus. AI enables you to pull out what makes your campus unique, to deliver more value for your students and to make your faculty members better faculty members. I realized that if you coach students to use AI and you are hands-on, you can use AI to do some of the most fantastic experiential learning. For example, this past semester, my students used AI to help write business proposals aimed at growing the Boys and Girls Club of Greater Lowell.

I didn’t understand that out of the gate. And not only that, but AI didn’t have those capabilities at first.

Q: Do you still worry that AI is a threat to faculty jobs?

A: AI is going to put some faculty out of a job, especially in fields where there’s more basic information. But it’s not going to be that I’m teaching one day and out of the job the next.

The faculty that it’s going to put out of a job are those that continue to resist and don’t experiment. They have to experiment and shift your perspective because AI is not going away. There is no endgame where five years from now there are faculty across the academy that say, “Wow, it’s good we didn’t buy into AI. It’s gone.” That’s never going to happen.

Q: What inspired you to develop the AI Campus Index?

A: Over the past year, I have talked to AI start-ups as well as faculty, campus leaders, provosts, chancellors and policymakers from the community college level all the way up to Stanford, Harvard and the University of Texas about AI.

And one of the things that came across from these conversations was that people were really anxious about AI, uncertain as to a path forward.

But the last thing I want to do is tell institutions that they better get on board because the AI train’s leaving. That’s just not the way this is going to happen. What’s going to happen is that over the next year or two, we’re going to see the broader AI sector’s bubble pop and reveal where the real value resides in the technology.

Right now, I’m telling institutions to pick something that is unique or special to their community college or research institution and use AI to draw out more value for their students. Don’t go hog wild and implement AI into every aspect of campus; there’s some risk involved, especially if you bring an AI vendor onto campus and they’re out of business 18 months later.

So, about six months ago, I started to think it would be nice if there was a way to catalog what institutions are doing across the academy. I wanted to get a sense of who’s doing what across higher education relative to AI.

Q: How does the AI Campus Index work?

A: It looks at six areas: AI in the classroom, AI in campus life, AI in operations, governance and AI, AI and research, and AI workforce readiness. We use Claude and some other proprietary algorithms to [score] each of those six buckets, which add up to 350 possible points.

There’s also some discretion on the weight of each bucket. For example, AI in the classroom is weighted heavier (85 possible points) than AI in campus life (45 possible points) because I think it’s very, very important right now.

In rating the classroom component, we ask questions like: Does the institution have an AI certificate? Is there an undergraduate degree, a graduate degree in AI? Are there efforts on campus that we can see relative to AI literacy? Are there dedicated AI courses on campus? And if there are these things, they get points, which add up to their AI in the classroom score.

Likewise, calculating the workforce-readiness score comes from asking if the college has a computing school. Do they have relationships with AI vendors? Is there an AI advisory board? Are there noted and documented workforce pipelines with AI companies in the area? Are there any AI-specific apprenticeships?

Q: What is the value of the AI Campus Index for institutions, students and faculty?

A: The rankings are good, but they’re not core to our value.

The real value is that an institution can see how their peer institutions are prioritizing their AI initiatives. It’s also helping institutions look internally and ask: Where are we placing our priorities? Where are we placing our resources? People are using the model to do an AI inventory on their own campus.

We also want to be a resource for parents who may look up an institution on the AI Campus Index and say, “This university isn’t really on board with the AI thing, and I don’t think my kid’s going to be prepared for the 21st-century economy where AI is going to be central.”

I hope that faculty start to become the leaders of the AI revolution on campus, and they could use the index to help them better understand what’s happening. It can help students make their decision about going into college and, as we start to evolve, get a sense of what they need to do. Students are leading the AI revolution on campus right now, but when faculty start to—and we start to catalog it—I think students will learn more from efforts like ours as to what’s going on on their campuses.