“Credits, credits, every where and no degrees are seen.” My apologies to Coleridge for reworking one of his most famous lines, but with the Some College, No Credential population now at 43 million and counting, it feels appropriate. In this week’s issue, we look at what one state is doing to help reduce that number for its residents. From there, we explore how majors have historically shaped future earnings and how AI might disrupt those patterns before closing with some timely advice on why clean data is essential before diving into an AI implementation.  

After reading today’s issue, share your thoughts about whether your institution has a strong data foundation for AI tools in the comments! 

Why So Few Students Complete Reverse Transfer 

From Giving Credit Where It’s Overdue | Inside Higher Ed

Reverse transfer is beneficial for both students (especially those who have not earned a credential) and colleges.  

Our Thoughts  

I think this is wonderful. Colorado’s move to award an associate credential to students who have made significant progress toward a bachelor’s degree is a rare policy that meets learners where they are and gives them proof of skills they have already earned. Recognizing learning through the Colorado Re-Engaged Initiative (CORE) will not solve every completion problem, but it directly addresses the growing group of adults with some college, no credential. That population is large and persistent, and a clear credential can help them reenter the labor market with momentum or return to college with renewed confidence. 

Programs such as these are part of how we begin to rebuild trust in higher education. If a student has earned 60 to 70 credits across two years, it should not be acceptable that their highest signal to employers is still a high school diploma. An associate credential for completed coursework formalizes gains in critical thinking, communication, and collaboration that come with sustained college study. Those skills are exactly what employers say will matter more as AI matures. Recent analyses place analytical thinking, resilience, creative thinking, and leadership near the top of in-demand skills through 2030, which makes interim credentials that certify these abilities more valuable, not less. 

Millions of adults have two years’ worth of college credit without a credential, and some are earning one without re-enrolling when states remove barriers and improve data sharing between institutions. Reverse transfer and CORE-style awards are not silver bullets, but they are pragmatic steps that acknowledge learning and shorten the distance between effort and recognition. In a moment when public skepticism runs high, that is the kind of student-first policy higher education needs more of. 

Majors Matter 

From Degrees boost earnings — but field of study matters, report finds | Higher Ed Dive

According to a new report from Georgetown University’s Center on Education and the Workforce (CEW), bachelor’s degrees still provide an economic boost for employees, but a student’s field of study significantly impacts their earnings potential.  

Our Thoughts  

The CEW report offers valuable context for families sorting through the wide range of degrees and majors offered by institutions, but remember, it’s only a snapshot. It shows what recent and prime-age workers earn today and, in the past, but not how tasks within those jobs will change as AI continues to spread across the economy. Reading it like a forecast can create a false sense of certainty about which majors are “safe,” especially given how quickly demand can shift when technology reshapes work.  

Most serious analyses frame AI as a reorganization of tasks rather than a simple replacement of jobs. That distinction matters because the earnings premium for certain majors tends to follow work that combines technical fluency with communication, collaboration, and judgment. Employers continue to name analytical thinking, leadership, social influence, and adaptability among the most in-demand skills. Ultimately, it may matter less which major appears on the diploma and more about the portfolio of skills a graduate can bring to dynamic work environments. 

At the same time, there is a credible case that AI could actually increase the value of the classic liberal arts degree when paired with strong AI literacy. Workers who marry technical fluency with writing, problem solving, and teamwork (skills long grounded in humanities and social science programs) may unlock more opportunities. A student who majored in history or psychology who is data and AI literate could outperform narrow training over a career. n the end, the smartest strategy isn’t to chase a single “future-proof” major, but to stack durable human skills with domain knowledge and the right technical literacies. That combination builds the resilience and adaptability employers consistently say they need most. 

Data Preparation Necessary for AI Deployment 

From Better data readiness opens the door to smarter AI in higher education | University Business 

Alexis Higgins argues that institutions must have a strong data foundation to make the most use of AI tools.    

Our Thoughts  

Higgins offers clear, practical advice. If leaders want real value from AI, the first move is not a model or a vendor pitch. It’s building a stronger, trusted data foundation. EDUCAUSE has been ringing that bell, pointing to data governance and data literacy as the work that makes everything else possible. AI can augment human insight, but only when your data house is in order. With a solid foundation of clean, connected, and well-governed data, institutions are far more likely to turn insights into action. 

On the data itself, predictive work only improves when institutions capture behavior with accuracy and consistency. Fragmentation is the quiet value killer. When financial aid, CRM, LMS, and advancement data do not align, you get brittle analysis and brittle AI. Identity resolution and consistent crosswalks matter more as agentic tools show up in campus operations, and most organizations are not yet data-ready for that shift. The pattern is the same everywhere: unified, accurate, governed data separates hype from help. 

None of this is glamorous, but it is what makes AI useful. The old rule still applies. Garbage in, garbage out. Institutions that invest in data quality and governance will see fewer surprises, safer deployments, and more trustworthy decisions. Start small, measure progress, and scale what works. The AI conversation will keep moving fast, but institutions that lay a strong data foundation now will be ready to turn that conversation into better, faster, and fairer decisions for students and for your campus.