From Tool to Agent: A Semi-Systematic Review of Human–AI Alignment and a Proposed Tiered Healing Ecosystem for Mental Health

Background: This study aims to systematically analyze the structural transition of AI in mental health, differentiating between passive tools and autonomous agents, and to propose a governance framework to facilitate responsible integration or mitigate integration risks. Methods: Employing a semi-systematic approach, we screened records from IEEE Xplore, PubMed, and ACM DL, ultimately analyzing 61 included studies. We track the transition from the first paradigm, AI-as-Tool (AI-T) to the second paradigm, AI-as-Agent (AI-A). Results: Early empirical evidence suggests that AI-A systems may assist in fostering preliminary working alliances and demonstrate potential for symptom reduction in controlled settings; however, their efficacy cannot currently be equated with, nor serve as a replacement for, standard low-intensity clinical care. Conclusions: To mitigate these risks, we propose the Tiered Human–AI Healing Ecosystem (THHE) for mental health. This framework utilizes dynamic autonomy modulation—automatically restricting AI agency based on real-time risk markers—to manage transitions between AI-led support and human-led care, promoting clinical safety.