Is Library-School AI Education Keeping Up with Employer Needs?

p strongLibrary-science faculty see AI fluency as increasingly important, yet course rules and curricular integration remain inconsistent&mdasha gap employers are likely to notice./strong/p p Primary Research Group found that roughly two-thirds of library-science faculty considered AI conversancy very or extremely important for students. Only about one-third, however, described their rules for student AI use as very or extremely clear. That mismatch can leave graduates enthusiastic about tools but uncertain about professional boundaries./p p Faculty generally favored conditional permission: AI could assist with supporting tasks when disclosed or cited, while submitting fully generated content was prohibited. Perceptions of misconduct varied widely. The median estimate of student cheating with AI was 10%, the average was 24%, and some respondents estimated rates as high as 100%. Nearly half had used either AI tools or detection tools themselves./p p Adoption was stronger among master's and doctoral programs, private institutions and faculty with heavier teaching loads. That suggests curriculum change may be shaped as much by program resources and practical workload as by philosophical support./p p A job-ready curriculum should connect AI to established library competencies: reference interviewing, metadata, privacy, copyright, assessment, accessibility, data work and vendor evaluation. Students should practice checking outputs and documenting decisions, not simply generating text. Programs that can show where AI belongs&mdashand where it does not&mdashwill give graduates a stronger professional identity than programs that treat the technology as either a universal solution or a forbidden shortcut./p p  /p