“Will Social Workers be Replaced By Robots?” Artificial Intelligence and the Construction of Future Professional Identity

Background and Purpose:

Artificial intelligence (AI) is increasingly entering social work practice, reshaping documentation systems, decision-support processes, service coordination, and therapeutic encounters. While existing scholarship has primarily focused on governance, bias, regulation, and ethical accountability, less attention has been devoted to how AI influences the evolving professional identity of social workers themselves. As algorithmic systems increasingly participate in knowledge production and decision-making, they raise not only technical and ethical concerns, but also foundational questions about expertise, authority, and the human core of professional practice. These developments shape how social workers exercise responsibility, interpret knowledge, and sustain trust within a democratic society. To fill this gap, this study examines practitioners’ narratives of professional becoming under conditions of technological transformation. This study is guided by the following research question: How do social workers conceptualize their future professional identity within an AI-integrated professional field?

Methods:

The study employed a qualitative phenomenological design to explore participants’ lived experiences and subjective meaning-making of AI integration into practice. Twenty social workers were recruited through professional networks and social media platforms. Participants represented diverse fields of practice, including family services, mental health rehabilitation, poverty and social inclusion, domestic violence, youth residential care, women’s health, elder services, and statutory welfare roles. Data were collected through in-depth semi-structured interviews conducted between September 2025 and March 2026. Interviews lasted 45–75 minutes, were audio-recorded, transcribed verbatim, and analyzed using reflexive thematic analysis.

Results:

Five interrelated themes emerged, illuminating how future professional identity is constructed in an AI-mediated landscape. First, AI was framed as enhancing efficiency and redistributing professional labor. Participants described AI as reducing administrative burdens and enabling greater focus on relational aspects of practice. Second, participants reaffirmed the centrality of professional discretion. While AI was acknowledged as analytically supportive, final judgment and interpretive responsibility were consistently positioned as irreducibly professional. Third, ethical gatekeeping emerged as a defining feature of future identity. Participants described heightened vigilance regarding confidentiality, data stewardship, and infrastructural risk, positioning themselves as moral custodians within data-driven systems. Fourth, professional authority was renegotiated within AI-mediated therapeutic relationships. As clients increasingly bring AI-generated interpretations into sessions, authority shifts from informational exclusivity toward dialogical mediation and relational legitimacy. Finally, participants articulated the irreplaceable human core of the profession. Embodied presence, emotional attunement, and even professional fallibility were framed as ontological foundations of social work that resist algorithmic substitution.

Conclusions and Implications:

Taken together, the findings suggest that AI functions less as a force of professional replacement and more as a catalyst for reflexive boundary-making. Social workers actively distinguish between augmentable and non-substitutable domains of practice, reconstructing professional identity across organizational, epistemic, ethical, relational, and ontological dimensions. The study contributes to emerging debates on AI in social work by shifting the focus from technological implementation to identity construction, offering a layered conceptualization of future professional identity as technologically engaged yet normatively bounded. These insights highlight the need to foreground ethical reflexivity and professional judgment in AI-integrated practice, ensuring that technological adoption remains aligned with core social work values and responsibilities.