Reconfigurative care and clinical responsibility in AI-mediated psychological care ecosystems

Artificial intelligence (AI) is becoming part of the organization of mental health support, from everyday self-monitoring and conversational assistance to screening, intervention, and service navigation. These developments are often framed through the question of whether AI can replace clinical psychological practice. This article argues that this question is too narrow. Psychological care consists of multiple forms of work through which distress is made intelligible, responded to, held in relation, opened to change, and connected to wider contexts of support. Using review-level evidence mapping and conceptual framework analysis, the study compares what information enters an AI operation, how it is transformed, what output is produced, who receives it, and which immediate action changes. The analysis constructed six clinical functions: assessment and case formulation; structured intervention and change support; relational responsiveness; holding unresolved experience; narrative and meaning formation and revision; and contextual and institutional connection. AI can widen access and make distress more visible, but it can also stabilize distress too quickly as a diagnosis, score, risk, intervention target, or self-management task. The article therefore proposes reconfigurative care as a normative principle intended to enable necessary judgment and safety action while preserving the ability of service users and care providers to revise interpretations, narratives, relations, and pathways of support. The future of AI-mediated psychological care depends less on whether machines can imitate clinicians than on whether care ecosystems can sustain clinical responsibility and revisability.