AI In Social Work Practice: Uses, Challenges, and Considerations

Background and Purpose: As artificial intelligence (AI) tools develop, there is a need to examine and understand how they may be applied in clinical social work practice. While studies have been conducted looking at the application of specific AI tools within social work (Goldkind, 2021; Kominkiewicz & O’Neil, 2025; Singer et al., 2023), this study addresses a gap in knowledge by surveying social work practitioners about how AI is being integrated (or not) within their agencies, and by identifying challenges, barriers, and areas for further development.

Methods: We recruited practicum instructors/agency partners in a northeastern state by emailing them directly. Respondents completed a survey about their use of AI, both with and without agency guidance, their clients’ use of AI, and their perceptions of AI use in social work practice. We asked respondents about their practice experience, agency setting, and client demographics. To address the research questions, we employed descriptive analyses, mixed-effect regression models, and qualitative content analysis of open-ended responses.

Results: All survey respondents (n = 50) indicated that they are currently supervising social work interns. In addition to currently supervising social work interns, 93% of respondents indicated they work directly with clients. Forty-three percent of respondents indicated their agencies were utilizing AI, with 72% of those responses indicating AI is used for documentation or case note summarization. In regard to organizational policy, 23% reported that their agency had a policy about AI use, 37% reported that their agency did not have a policy about AI use, and 40% were not sure.. Half (50%) reported that their clients are using AI based tools to support their mental and behavioral health and 38% believed that AI tools are somewhat helpful for their clients. Finally, 70% of respondents indicated that it was very or extremely important for social work students to be trained and educated on AI. Qualitative themes included concerns around confidentiality/privacy, data security, ethics and AI’s possible impact on critical thinking and skill development for early career social workers

Conclusions and Implications: As technology and innovation create opportunities in social work, we must have conversations around how tools such as AI connect to social work values. This study is one of the first to explore the application of AI in clinical practice settings on a large scale. It demonstrated that agencies that are implementing AI are using it for documentation and case note summarization, however most respondents indicate ethical and data privacy concerns as a primary barrier to implementing AI. This underscores the need for increased research and practice guidance on how to utilize AI for documentation while being cognizant of ethical and privacy concerns. As noted, an overwhelming majority of respondents indicated the need for social work students to obtain knowledge about AI. These findings highlight the need for increased training, education, and support for social workers and social work students around AI literacy.