Learning-management system vendors and higher-education analysts urged a shift in assessment strategy after concluding detection of agentic AI and autonomous assistants is unreliable. Blackboard executives argued institutions should redesign assessment and grading practices rather than rely on detection tools that cannot consistently identify agentic AI. Simultaneously, campus-focused AI vulnerability analyses flagged which higher-education roles are most exposed to automation—administrative tasks, certain advising functions, and routine grading among them—prompting academic leaders to reassess staffing models, upskilling plans, and curricular design. Provosts and academic technologists should escalate plans to integrate AI literacy into staff development, redesign assessments to privilege authentic, supervised demonstrations of learning, and pursue cross-functional governance to manage agentic AI risks.