Towards deployment-centric multimodal AI beyond vision and language

Liu, Xianyuan ORCID: https://orcid.org/0000-0002-3084-519X; Zhang, Jiayang; Zhou, Shuo ORCID: https://orcid.org/0000-0002-8069-2814; van der Plas, Thijs L. ORCID: https://orcid.org/0000-0001-5490-1785; Vijayaraghavan, Avish ORCID: https://orcid.org/0009-0007-2821-1917; Grishina, Anastasiia; Zhuang, Mengdie; Schofield, Daniel; Tomlinson, Christopher ORCID: https://orcid.org/0000-0002-0903-5395; Wang, Yuhan ORCID: https://orcid.org/0000-0003-0718-3359; Li, Ruizhe ORCID: https://orcid.org/0000-0003-2512-845X; van Zeeland, Louisa ORCID: https://orcid.org/0009-0005-0392-4377; Tabakhi, Sina ORCID: https://orcid.org/0000-0002-3075-7907; Demeocq, Cyndie ORCID: https://orcid.org/0009-0000-7713-3707; Li, Xiang; Das, Arunav ORCID: https://orcid.org/0009-0008-9989-1718; Timmerman, Orlando; Baldwin-McDonald, Thomas ORCID: https://orcid.org/0000-0001-7301-4399; Wu, Jinge; Bai, Peizhen ORCID: https://orcid.org/0000-0003-3027-5518; Al Sahili, Zahraa; Alwazzan, Omnia ORCID: https://orcid.org/0000-0001-7416-1622; Do, Thao N. ORCID: https://orcid.org/0000-0002-0015-892X; Suvon, Mohammod N. I. ORCID: https://orcid.org/0000-0001-9962-315X; Wang, Angeline ORCID: https://orcid.org/0009-0002-0845-6136; Cipolina-Kun, Lucia; Moretti, Luigi A. ORCID: https://orcid.org/0009-0002-6180-0565; Farndale, Lucas ORCID: https://orcid.org/0009-0003-3667-2001; Jain, Nitisha ORCID: https://orcid.org/0000-0002-7429-7949; Efremova, Natalia ORCID: https://orcid.org/0000-0003-4853-9550; Ge, Yan; Varela, Marta; Lam, Hak-Keung; Celiktutan, Oya; Evans, Ben R. ORCID: https://orcid.org/0000-0003-0643-526X; Coca-Castro, Alejandro ORCID: https://orcid.org/0000-0002-9264-1539; Wu, Honghan; Abdallah, Zahraa S.; Chen, Chen; Danchev, Valentin ORCID: https://orcid.org/0000-0002-7563-0168; Tkachenko, Nataliya; Lu, Lei; Zhu, Tingting ORCID: https://orcid.org/0000-0002-1552-5630; Slabaugh, Gregory G.; Moore, Roger K.; Cheung, William K. ORCID: https://orcid.org/0000-0002-7428-2050; Charlton, Peter H.; Lu, Haiping ORCID: https://orcid.org/0000-0002-0349-2181. 2025 Towards deployment-centric multimodal AI beyond vision and language. Nature Machine Intelligence, 7 (10). 1612-1624. 10.1038/s42256-025-01116-5

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Abstract/Summary

Multimodal artificial intelligence (AI) integrates diverse types of data via machine learning to improve understanding, prediction and decision-making across disciplines such as healthcare, science and engineering. However, most multimodal AI advances focus on models for vision and language data, and their deployability remains a key challenge. We advocate a deployment-centric workflow that incorporates deployment constraints early on to reduce the likelihood of undeployable solutions, complementing data-centric and model-centric approaches. We also emphasize deeper integration across multiple levels of multimodality through stakeholder engagement and interdisciplinary collaboration to broaden the research scope beyond vision and language. To facilitate this approach, we identify common multimodal-AI-specific challenges shared across disciplines and examine three real-world use cases: pandemic response, self-driving car design and climate change adaptation, drawing expertise from healthcare, social science, engineering, science, sustainability and finance. By fostering interdisciplinary dialogue and open research practices, our community can accelerate deployment-centric development for broad societal impact.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	10.1038/s42256-025-01116-5
ISSN:	2522-5839
Additional Keywords:	Computer science, Information technology
NORA Subject Terms:	Electronics, Engineering and Technology Health Computer Science Data and Information
Date made live:	30 Oct 2025 14:35 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/540479

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