Artificial intelligence in social work: A rapid review

Authors

• Samuel Salovaara University of Lapland, Rovaniemi https://orcid.org/0000-0001-7818-8427
• Marjo Outila University of Lapland, Rovaniemi https://orcid.org/0000-0002-1272-2196
• Ville Heilala University of Jyväskylä, Jyväskylä https://orcid.org/0000-0003-2068-2777
• Sanna Hautala University of Lapland, Rovaniemi https://orcid.org/0009-0000-6876-9623

DOI:

https://doi.org/10.23996/fjhw.179073

Keywords:

artificial intelligence [http://www.yso.fi/onto/yso/p2616], social work [http://www.yso.fi/onto/yso/p3286], systematic literature review

Abstract

Artificial intelligence (AI) is currently transforming work, education, and societal institutions, and its applications extend to social work as well. This study mapped the current state of research on AI and social work by conducting a rapid review across seven databases and analyzing 58 relevant scholarly articles. The review identifies how AI technologies are defined in social work research, the domains in which they are applied, and the documented consequences of AI use in social work.

The findings indicate that international research on this topic is growing rapidly and is concentrated in North America. In social work research, AI is examined particularly in relation to education, while studies focusing on practice emphasise child protection. The reviewed literature covers numerous applications of AI in social work and describes potential benefits for the development of services, education, administration, and research, alongside recognised risks and ethical challenges.

Although AI offers notable opportunities for social work, including more efficient processes, reduced workload and strengthened evidence‑based practice, it also entails significant risks for vulnerable populations. Algorithms may amplify existing data biases, reduce decision‑making transparency and narrow professional discretion, thereby increasing the risk of discrimination, inequality and privacy violations. The results indicate that the contextual complexity of social work resists overly simplistic technical solutions and requires thorough ethical assessment as well as critical scrutiny of data and AI models prior to implementation. Responsible use further demands clear guidelines, interdisciplinary collaboration and strong critical AI literacy among social workers. AI is most suitable for social work as a complementary tool that can create added value when its role and technical design are thoughtfully defined. The review underscores the need for interdisciplinary research that integrates ethical considerations and core social work values in the responsible adoption of AI.