With the recent release of the DeepSeek model, AI is once again in the spotlight. In this week’s issue, we examine key takeaways from the 2025 EDUCAUSE AI Landscape Study and their implications for institutions. Then, we explore UC San Diego’s AI-powered assistants and their potential to transform data accessibility. Finally, we wrap up with a discussion on new research analyzing the best time to measure a graduate’s earnings.  

After reading today’s issue, use the comments section to tell us about your institution’s AI strategy. 

EDUCAUSE AI Study 

From 2025 EDUCAUSE AI Landscape Study: Into the Digital AI Divide | EDUCAUSE  

The higher education community continues to grapple with questions related to using artificial intelligence (AI) in learning and work. In support of these efforts, the 2025 EDUCAUSE AI Landscape Study summarizes our community’s sentiments and experiences related to strategy and leadership, policies and guidelines, use cases, the higher education workforce, and the institutional digital divide.   

Our Thoughts 

Regular readers know how much I appreciate EDUCAUSE studies because they provide valuable insights into the current state of key topics. The AI Landscape Study offers a critical look at how institutions are approaching AI strategy, workforce development, and policy adoption. The findings indicate a growing recognition of AI as a strategic priority, yet many institutions struggle with implementation, particularly in training, funding, and governance. Notably, while faculty training is a focus for many institutions, students are adopting AI at a faster rate, raising important questions about whether faculty are truly prepared to guide students in responsible and effective AI use. 

This report also highlights a widening digital AI divide between institutions of different sizes. While leaders at smaller institutions share the same optimism about AI as their peers at larger universities, their resources for AI adoption lag significantly. This disparity raises concerns about equity in AI-driven education and whether underfunded institutions can remain competitive. The findings suggest that AI will increasingly shape the future of teaching, learning, and institutional operations, yet many colleges are reacting to AI rather than proactively integrating it into long-term planning. As AI evolves, institutions that fail to develop structured, well-funded AI strategies risk falling behind in both academic innovation and workforce preparedness.  

The EDUCAUSE study offers a roadmap for institutions to assess their AI readiness and push for policies that ensure AI benefits all members of the academic community, not just the best-resourced institutions. 

Building AI Agents 

From Ushering in a New Era of AI-Driven Data Insights at UC San Diego | EDUCAUSE Review  

TritonGPT, developed at UC San Diego, is a suite of AI-powered assistants designed to streamline administrative tasks, enhance productivity, and provide institution-specific insights by retrieving, summarizing, and generating content securely.   

Our Thoughts 

While I’m still sorting out my thoughts on AI and its impact on education, I found this article about UC San Diego’s AI agents fascinating. It presents a compelling case for how AI-driven natural language interfaces can democratize data access and enhance operational efficiency. In an era where institutions are overflowing with data but often lack meaningful insights, improving data accessibility for faculty and staff can help turn raw numbers into actionable strategies.  

Beyond showcasing AI’s potential, the authors’ openness and collaborative approach provide a valuable perspective on how institutions can navigate AI’s expanding role in higher education. While AI-powered platforms hold promise, concerns about accuracy and data privacy persist. By sharing experiences and best practices, we can learn from one another and address these challenges together.  

AI-driven analytics and conversational interfaces may soon reshape how users interact with data, making strong data governance and literacy more important than ever. After all, AI is only as effective as the data it relies on. For institutional leaders, UC San Diego’s work offers both inspiration and a practical guide for navigating the evolving intersection of AI and higher education. 

Measuring the Earnings of College Graduates 

From Want to measure how much college graduates make? Timing matters. | Higher Ed Dive  

Recent research from the Urban Institute found that the timing of when a graduate’s earnings are measured affects the perceived value of the credential earned.  

Our Thoughts  

Given the current political climate and public perception of the higher education sector, we should pay close attention to research like this that seeks to better understand the return on investment for students. Perhaps unsurprisingly, the timing of earnings measurements can significantly shape how academic programs are assessed. If earnings are measured too early, the data may not fully reflect the long-term value of a degree, potentially undervaluing programs with strong upward career trajectories. Conversely, waiting too long could allow institutions to continue operating without timely accountability, possibly enabling ineffective programs to persist without intervention. These conflicting ideas are particularly relevant as both major political parties push for more stringent accountability measures for higher education.  

While associate degree holders initially earn salaries comparable to bachelor’s graduates, the gap widens over time, reinforcing long-held economic arguments in favor of bachelor’s degrees. However, the findings also highlight the importance of field-specific trajectories, suggesting that institutions need to think beyond simplistic earnings metrics when demonstrating value. Factors such as career pathways, industry demand, and regional labor markets must also be considered. As policymakers continue to refine accountability frameworks, higher education leaders must be proactive in shaping how success is measured to ensure institutions and programs are evaluated fairly.