In my past life working at institutions, whenever we were adopting new software, I always spent a few minutes during information or training sessions giving people space to mentally and emotionally process this change. They were free to say whatever they wanted about it. They loved it. They hated it. They worried about the impact of the new technology on the culture of the campus. I found that providing people with an outlet to talk through those reactions helped me better understand where the real friction was and how to navigate the technology shift more thoughtfully. That’s probably why, in this week’s issue, I featured an article that adapts the Kübler-Ross framework to help guide people through AI adoption. From there, we look at two interrelated articles on why students pursue noncredit credentials and what the data say about the payoff of earning a degree. 

After reading today’s issue, share your experiences guiding others through AI adoption in the comments! 

Guiding Staff Through AI Adoption 

From Use the five stages of grief to guide academic staff through AI adoption | Times Higher Education 

Using the Kübler-Ross framework as inspiration, the authors offer advice for supporting staff through the current AI reality.  

Our Thoughts  

The main idea I took away from this piece is that some of what we call “AI resistance” may not actually be about the tool. Instead, it may be about loss: the loss of familiar assessment practices, the loss of confidence in what counts as student work, and for some people, the loss of a professional identity built around expertise and craft. Framing that as an emotional change curve, rather than a pedagogical one, is a practical way to help leaders stop treating every concern as a technical problem to be solved. 

Even if you do not love the Kübler-Ross model (and you shouldn’t treat it like a neat, linear checklist), it works as a conversation starter because it normalizes what people are feeling. Most of us move in and out of these stages, sometimes in the same week, and Kübler-Ross herself emphasized that the stages are not experienced in a fixed order. 

Although the authors frame their article for faculty, I think the same emotional dynamics apply to staff as well. In many operational areas, AI is already showing up inside the tools people use every day, and the change is often happening faster than norms, training, or governance can keep up. EDUCAUSE’s recent work on AI and the higher ed workforce shows that adoption is widespread, but clarity and confidence lag behind, which is exactly the gap where anxiety and risk begin to compound. 

Ultimately, as you continue to explore AI adoption on your campus, you don’t want to turn its use into either compliance theater or a culture war. The tone we use in conversations sets the stage for how AI use is perceived on your campus. If the message is “get on board” or “ban it,” people will retreat into denial or resentment. If the message is “let’s talk honestly and learn together,” you create the conditions for real adaptation, which is the only outcome that scales. 

Noncredit Student Goals 

From Understanding Noncredit Students’ Goals and Motivations | Inside Higher Ed 

A new report from Rutgers University’s Education and Employment Research Center looks at the reasons why students pursue noncredit credentials. 

Our Thoughts  

This qualitative study demonstrates the importance of actually talking with students. Although a small study, it is immensely valuable to hear the stories of students enrolled in noncredit programs to better understand what these students want out of postsecondary education. When 71 percent of interviewees have tried college before, it reframes noncredit as less of an “alternative” and more of a re-entry point for people who hit predictable barriers the first time around. 

The timing of this report is also particularly important. With Workforce Pell approaching, we are going to see more attention, funding, and scrutiny aimed at short-term workforce pathways. If a meaningful share of those programs are delivered through (or alongside) noncredit divisions, then understanding motivations like “I need something that fits my life right now” becomes operationally important, not just academically interesting. If institutions treat noncredit as a side operation instead of an integrated part of the student journey, we will miss the opportunity to build clearer bridges into credit, and we risk failing the students who want a pathway but do not always understand which programs actually connect to their goals. 

It also matters for the Some College, No Credential population. The Clearinghouse’s most recent report puts the national SCNC population at 43.1 million, including 37.6 million adults under 65, at the start of the 2023–24 academic year. Noncredit programs can be a practical way back in, especially when they are short, affordable, and aligned to jobs. But access alone is not enough. The key is ensuring these programs lead somewhere real, either a good job quickly or a credible on-ramp to further education. 

The Payoff of Earning a Degree 

From Report Tracks Not Just Degrees, But Payoff | Inside Higher Ed 

The Lumina Foundation’s recent A Stronger Nation report found that 43.6% of U.S. adults aged 25–64 in the workforce hold a college degree or other credential and earn more than those with only a high school diploma. 

Our Thoughts  

I like this direction from Lumina because it moves the conversation about college value out of the abstract and into something concrete and measurable. Their new baseline shows that 43.6% of adults ages 25 to 64 in the labor force hold a degree or workforce credential beyond high school and earn at least 15% more than adults with only a high school diploma. That is a meaningful signal of progress and a much clearer story than attainment alone. 

I also appreciate that the benchmark is intentionally simple. It is not perfect, but it is consistent, and consistency is what makes trendlines usable over time. As the public conversation continues to shift toward ROI, we need more measures like this that allow for comparison without pretending that every credential, program, or pathway is interchangeable. 

Finally, it is a net positive when this level of data and accountability comes from a neutral third party. While federal data collection efforts can create important guardrails, independent benchmarking gives the sector a way to demonstrate progress and surface gaps without the exercise feeling punitive. If we want to rebuild public trust, we are going to need more of this kind of transparent, outcomes-based storytelling that is grounded in data but accessible to the public.