The ECNP AI in mental health network – a european-led coordinated effort for clinical AI implementation

Artificial intelligence (AI) is advancing rapidly across mental health research, with applications ranging from multimodal discovery, prediction and treatment stratification to clinical decision support, digital therapeutics and generative AI. Despite this progress, translation into routine clinical care remains limited. Persistent barriers include fragmented evidence, variable methodological quality, poor external validation, uncertain regulatory pathways, limited implementation infrastructure, and insufficient coordination between researchers, clinicians, patients, regulators, funders, and healthcare systems.

The ECNP AI in Mental Health Network was established to address these challenges through a coordinated European platform spanning the full translational pathway from scientific discovery to clinical implementation. Its activities are structured around seven interconnected domains: discovery and mechanisms; measurement, phenotyping and data ecosystems; prediction, stratification and precision psychiatry; interventions and clinical decision support; evidence generation and evaluation; knowledge systems and large language models; and implementation, governance and responsible AI.

This lecture will introduce the Network’s structure, objectives and initial programme of work. Key priorities include identifying AI applications with genuine clinical readiness, strengthening standards for validation and evaluation, supporting responsible implementation, improving interoperability and cross-centre collaboration, and creating stronger links with regulators, funders, health systems and people with lived experience. Initial activities include a cross-disciplinary review, a shared AI in mental health resource hub, and strategic workshops designed to generate practical recommendations and collaborative initiatives.

The presentation will conclude by framing the central challenge for the panel: how can Europe move from promising AI research towards safe, scalable, equitable and clinically meaningful implementation?