Translating AI research into reality: summary of the 2025 voice AI Symposium and Hackathon

Journal article : Review

The 2025 Voice AI Symposium represented a transition from conceptual research to clinical implementation in vocal biomarker science. Hosted by the NIH-funded Bridge2AI-Voice consortium, the meeting convened global experts to address the methodological, ethical, and translational challenges of integrating voice-based artificial intelligence (AI) into healthcare. This mini-review synthesizes symposium insights across six domains: multimodal integration, FAIR (Findable, Accessible, Interoperable, Reusable) and CARE (Collective Benefit, Authority to Control, Responsibility, Ethics) data governance, clinical translation, interdisciplinary training, and cross-sector innovation. Research presented demonstrated voice as a latent, multimodal biomarker reflecting neurological, cardiopulmonary, and psychological states, while discussions emphasized ethical data practices and human-centered design. The implementation-focused panels underscored the importance of workflow alignment and usability for adoption in real-world care. Collectively, the symposium reflects a field advancing toward translational readiness and ethical accountability, positioning voice AI as a scalable, inclusive tool for next-generation healthcare.

Authors: Salvi Cruz, S; Toghranegar, J; Malin, B; Mehra, T; MacDonald, B

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Frontiers Media
• Journal: Frontiers in Digital Health
• Volume: 8
• Article number: 1754426
• Publication date: 2026-03-16
• Acceptance date: 2026-02-13
• DOI: 10.3389/fdgth.2026.1754426
• EISSN: 2673-253X
• ISSN: 2673-253X
• Language: English
• Keywords: voice AI; multimodal data; artificial intelligence; clinical translation; vocal biomarkers
• Subtype: Review