2025 wasn’t just another year for higher education; it was the moment theory turned into reality. Institutions stopped planning for AI and started deploying it. Things broke. New tools emerged. And long-standing assumptions about how students learn, how credentials work, and who controls educational pathways began to crack.

In this episode of the Inside the Learning Experience Podcast, we dive deep into our 2025 End of Year Impact Report to examine how AI is being used to tackle higher education’s most persistent wicked problems.

What happens when students don’t get the help they need, despite institutions offering robust support services? In this episode of Inside the Learning Experience, WGU Labs researchers unpack what they’re learning from students as they design Stu, an AI-powered student support tool built to proactively connect learners with the right resources at the right time.

Betheny Gross is joined by senior research scientists Youngki Hong and Stephanie Reeves to explore why student support services are underutilized, how barriers like belonging, stigma, and awareness shape help-seeking behaviors, and where AI can and can’t step in. Drawing on large-scale surveys, interviews, and early user testing, the conversation highlights critical design insights, equity considerations, and open research questions around personalization, trust, and the role of AI in supporting motivation, belonging, and long-term student success.

What does it take to build an AI mentor—and what data should power it?

In this episode of Inside the Learning Experience, WGU Labs explores how AI can support students by scaling mentoring, personalizing guidance, and connecting learners to the right resources at the right time.