FACULTY READINESS AND PROFESSIONAL DEVELOPMENT FOR AI INTEGRATION IN HIGHER EDUCATION

Abstract

Universities have adopted artificial intelligence considerably faster than they have prepared their teachers to use it. Policies, platforms and integrity rules have multiplied, yet many academics still report little confidence in redesigning their teaching around AI. This chapter argues that faculty readiness is not a preliminary step to be completed before integration begins; it is the main factor deciding whether integration improves teaching or merely adds technology. We describe readiness as having five connected parts — technical skill, pedagogical judgement, ethical understanding, confidence and attitude, and supportive institutional conditions — of which most training programmes address only the first. Drawing on recent higher education research and on longer-established work about how teachers change, the chapter sets out a four-stage path running from awareness through experimentation and pedagogical redesign to scholarly leadership. Six principles for designing faculty development follow from it: teach within disciplines, begin with pedagogy rather than tools, sustain the work over time, build peer communities, treat AI critically rather than promotionally, and reward participation. Where teaching genuinely calls for AI, we argue, academics should be equipped to adopt it, and faculty development is the means by which institutional strategy becomes classroom practice.