From resistance to integration: AI in social work education

The integration of artificial intelligence (AI) into social work education continues to have some resistance. Through a cross-sectional survey of social work instructors, we explore attitudes, barriers to, and characteristics of AI adoption, while addressing the unique ethical and professional considerations specific to social work education. Overall, our findings suggest a readiness paradox where high familiarity with AI coexists with moderate confidence in adaptation, creating thoughtful innovation while preserving core professional values. More specifically, the findings indicate that AI adoption in social work education is individually motivated, driven primarily by specific pedagogical or scholarly benefits; is policy influenced, shaped more by the clarity and perceived helpfulness of institutional guidance than by its mere existence; and is not socially driven, with adoption largely unaffected by perceived peer norms or visible professional trends. These findings reflect a landscape of isolated innovators rather than a coordinated movement, underscoring the need for strategies that can scale adoption. To move beyond scattered experimentation, institutions should prioritize creating opportunities for visibility, peer learning, and community-building, such as faculty showcases, peer-led workshops, and communities of practice, while also providing clear, supportive, and actionable policies.