{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T19:16:47Z","timestamp":1772911007767,"version":"3.50.1"},"reference-count":59,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T00:00:00Z","timestamp":1751328000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"ALGORITMI Centre"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Applied Sciences"],"abstract":"<jats:p>The transition to Industry 5.0 highlights the growing integration of Robotic Process Automation (RPA) and Artificial Intelligence (AI) in industrial ecosystems. However, adoption remains fragmented, lacking standardized frameworks to align intelligent automation with human-centric principles. While RPA improves operational efficiency and AI enhances cognitive decision-making, challenges such as organizational resistance, interoperability, and ethical governance hinder scalable and sustainable implementation. The envisioned scenario involves seamless RPA-AI integration, fostering human\u2013machine collaboration, operational resilience, and sustainability. Expected outcomes include (1) hyperautomation for efficiency gains, (2) agile, data-driven decision-making, (3) sustainable resource optimization, and (4) an upskilled workforce focusing on innovation. This study proposes a structured five-stage framework for RPA-AI deployment in Industry 5.0, combining automation, cognitive enhancement, and human\u2013machine symbiosis. A systematic literature review (PICO method) identifies gaps and supports the framework\u2019s design, validated through operational, human-impact, and sustainability metrics. Incorporating ethical governance and continuous upskilling, the model ensures technological advancement aligns with societal and environmental values. Results demonstrate its potential as a roadmap for responsible digital transformation, balancing efficiency with human-centricity. Future research should focus on empirical validation and sector-specific adaptations.<\/jats:p>","DOI":"10.3390\/app15137402","type":"journal-article","created":{"date-parts":[[2025,7,1]],"date-time":"2025-07-01T09:29:01Z","timestamp":1751362141000},"page":"7402","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["A Framework for Integrating Robotic Process Automation with Artificial Intelligence Applied to Industry 5.0"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5267-5996","authenticated-orcid":false,"given":"Leonel","family":"Patr\u00edcio","sequence":"first","affiliation":[{"name":"Department of Production and Systems, Algoritmi\/LASI, University of Minho, 4804-533 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2299-1859","authenticated-orcid":false,"given":"Leonilde","family":"Varela","sequence":"additional","affiliation":[{"name":"Department of Production and Systems, Algoritmi\/LASI, University of Minho, 4804-533 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5040-0403","authenticated-orcid":false,"given":"Zilda","family":"Silveira","sequence":"additional","affiliation":[{"name":"Department of Mechanical Engineering, Sao Carlos School of Engineering, University of Sao Paulo, Sao Paulo 13566-590, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4202-5551","authenticated-orcid":false,"given":"Carlos","family":"Felgueiras","sequence":"additional","affiliation":[{"name":"ISEP\u2014Instituto Superior de Engenharia do Porto, Polytechnic of Porto, Rua Dr. Ant\u00f3nio Bernardino de Almeida, 4249-015 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7809-5554","authenticated-orcid":false,"given":"Filipe","family":"Pereira","sequence":"additional","affiliation":[{"name":"INEGI\u2014Institute of Science and Innovation in Mechanical and Industrial Engineering, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal"},{"name":"MEtRICs Research Center, School of Engineering, University of Minho, Campus of Azur\u00e9m, 4800-058 Guimar\u00e3es, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/j.jmsy.2024.02.010","article-title":"Unlocking the power of industrial artificial intelligence towards Industry 5.0: Insights, pathways, and challenges","volume":"73","author":"Leng","year":"2024","journal-title":"J. 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