As institutions navigate the uncharted territory of artificial intelligence, they're taking varied approaches—from revamping curricula to developing new strategic frameworks. The divergent tactics highlight a broader tension in higher education: how to embrace AI's transformative…
University research leaders face mounting pressure to address the growing presence of AI-generated content in academic publications, as concerns mount that low-quality material could undermine practitioner trust in education research. Institutional strategies for maintaining rese…
A new Gallup survey confirms what many university leaders have suspected: AI tools have become routine for college students, with usage rates remaining high even at institutions that have implemented restrictions. The findings suggest that campus policies may need to evolve from …
The proliferation of AI writing tools presents university leaders with an unprecedented academic integrity challenge that traditional plagiarism detection alone cannot solve. Institutional responses must balance fostering technological literacy with maintaining rigorous standards…
As the college-age population continues its steady decline, university leaders are grappling with shrinking enrollments and tighter budgets. Many are now turning to AI tools to streamline operations and attract prospective students, though questions remain about whether technolog…
Students are increasingly questioning the value of traditional majors as AI reshapes career expectations, forcing institutions to confront difficult questions about curriculum relevance. University leaders must balance responding to these concerns quickly while maintaining academ…
University faculty are reporting that AI-assisted student work is increasingly homogeneous, raising fresh questions about how institutions can preserve critical thinking development while integrating new technologies. Administrators face the delicate task of establishing policies…
This analysis argues that faculty critiques of AI output may be misdirected—the issue isn't the technology's fundamental capabilities but rather how it's being applied in academic contexts, a distinction university leaders should consider when developing institutional AI strategi…
University leaders are grappling with new data showing that graduates in psychology and education—fields long considered resistant to automation—are now seeing negative returns on their degrees, raising urgent questions about curriculum relevance and career guidance. The shift su…
A wave of AI-related legislation is sweeping through statehouses, with 134 bills now pending across 31 states—many targeting student data privacy protections. University administrators should track these evolving regulations closely as they could reshape how institutions deploy A…
The conversation has shifted from whether to integrate AI into curricula to how quickly we can prepare graduates for a workforce where AI fluency is as fundamental as computer literacy was two decades ago. Employers across sectors—healthcare, finance, manufacturing, public servic…
After three decades of watching technology reshape the classroom, I've seen this pattern before—students discovering a shortcut that feels like a solution, then gradually losing the ability to navigate without it. AI tools are no different. The difference now is speed. What once …
Here's something most humanities scholars never hear in graduate school: the analytical frameworks, research methodologies, and deep subject expertise you've spent years developing are exactly what businesses and organizations are willing to pay for. The gap isn't your knowledge—…
Here's something that surprises most people when they first learn it: the more you limit your AI prompt, the better the output tends to be. It feels backwards—you'd think giving a tool more freedom would produce more creative or useful results. But in practice, constraints actual…