{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T02:11:35Z","timestamp":1773367895659,"version":"3.50.1"},"reference-count":80,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T00:00:00Z","timestamp":1773273600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Robotics"],"abstract":"<jats:p>Generative Artificial Intelligence (GenAI), particularly Foundation Models (FMs), has recently become a key component of Industry 5.0. Despite growing interest in integrating these technologies into industrial environments, comprehensive analyses of the socio-technical opportunities and challenges of deploying these emerging AI systems in real-world settings remain limited. This article proposes a socio-technical conceptual perspective, termed Responsible Agentic Robotics (RAR), which structures the lifecycle deployment of agentic AI-enabled robotic systems around three core layers: context, design, and value. Additionally, this article presents a brief review of 21 peer-reviewed studies published between 2023 and 2025 (post-ChatGPT era) on FMs and agentic AI-enabled Human\u2013Robot Collaboration (HRC) in industrial assembly\/disassembly environments. The results indicate that existing research remains predominantly technology-centric, with a strong emphasis on enhancing robot autonomy, while comparatively limited attention is devoted to human-centered and responsible practices. Moreover, empirical evaluations of human, social, and sustainability dimensions, such as worker empowerment, human factors, well-being, inclusivity, resource utilization, and environmental impact, are rarely conducted and poorly discussed. This article concludes by identifying key socio-technical gaps, outlining future research directions.<\/jats:p>","DOI":"10.3390\/robotics15030058","type":"journal-article","created":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T13:12:24Z","timestamp":1773321144000},"page":"58","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["From Large Language Models to Agentic AI in Industry 5.0 and the Post-ChatGPT Era: A Socio-Technical Framework and Review on Human\u2013Robot Collaboration"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5444-377X","authenticated-orcid":false,"given":"Enrique","family":"Coronado","sequence":"first","affiliation":[{"name":"National Institute of Advanced Industrial Science and Technology (AIST), Tokyo 135-0064, Japan"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Li, D., Jin, Y., Sun, Y., A, Y., Yu, H., Shi, J., Hao, X., Hao, P., Liu, H., and Li, X. 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