Across U.S. campuses, AI adoption is prompting unease rather than excitement, as leaders, faculty, and students grapple with rapid change. Students in computer‑science tracks fear AI will erode future job prospects, while staff worry about automation replacing knowledge‑work roles. Educators cite a lack of suitable pedagogy and rising academic‑integrity challenges as AI reshapes teaching and assessment. Meanwhile, fragmented governance and competing stakeholder priorities leave institutions uncertain about accountability, data security, and policy direction.
Higher education must shift from siloed, traditional models to connected ecosystems that blend work and learning, leverage data as strategic oxygen, and eliminate digital sprawl. Leaders can use platforms for work‑integrated learning, predictive analytics, and system consolidation to improve retention,...