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.
Keywords: artificial intelligence; clinical translation; multimodal data; vocal biomarkers; voice AI.
© 2026 Salvi Cruz, Toghranegar, Malin, Mehra, MacDonald, Speights, Noufi, Fossat, Fagherrazi, Cummins, Elbeji, Blatter, Gelbard, Arienzo, Baur, Wetstone, Peller, Au, Botha, Lahav, Hemmerling, Catania, Anibal, Saha, Coleman, Gallois, Avila Martinez, Mahapatra, Singh Sara, Mathur, Patel, Zieliński, Kourtis, Lerner-Ellis, Cong, Ngo, Talkar, Hale, Comito, Ghosh, Watts, Bedrick, Powell, Bélisle-Pipon, Krussel, Mahapatra, Bahr, Hanna, Kostelnik, Dorsey, John, Curp, Rameau, The Bridge2AI-Voice Consortium and Bensoussan.