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Journal for Social Work Scholar-Practitioners

Abstract

As Domestic Violence (DV) and Intimate Partner Violence (IPV) organizations work to meet the complex needs of survivors, the realities facing the workforce demand closer examination. DV/IPV advocates must navigate high caseloads, persistent exposure to trauma, limited organizational resources, and extensive administrative responsibilities that often overshadow the relational and advocacy work central to survivor support. Given that 40–75% of DV/IPV staff experience moderate to high burnout (Kulkarni et al., 2013; Slattery & Goodman, 2009), exploration and use of new technological tools, such as generative artificial intelligence (AI), become a consideration in how organizations might offer support to DV/IPV staff in reducing workload, contributing to the discussion on preventing burnout. Research in other sectors suggests that AI technologies can reduce administrative burdens, improve efficiency, and allow workers to focus more on meaningful aspects of their work (Brynjolfsson & McAfee, 2017). While AI integration offers clear benefits, it also raises significant concerns, including deskilling, overreliance, and the marginalization of professional expertise (Pavuluri et al., 2024). Reamer (2025) explains, it is necessary to develop a clear understanding of how AI is being used across the behavioral health settings, the ethical challenges it raises, evidence-informed best practices, and practical risk-management strategies to safeguard both clients and workers. Therefore, as AI integration becomes more prominent in social work settings, a deeper look at the concept of AI literacy among the DV/IPV workforce becomes vital to ensure AI use does not compromise ethics, worker expertise and service delivery (Reamer, 2025).

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