{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T00:57:44Z","timestamp":1775869064176,"version":"3.50.1"},"reference-count":109,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Research Unit on Governance, Competitive-ness and Public Policies","award":["UIDB\/04058\/2020"],"award-info":[{"award-number":["UIDB\/04058\/2020"]}]},{"name":"Research Unit on Governance, Competitive-ness and Public Policies","award":["UIDP\/04058\/2020"],"award-info":[{"award-number":["UIDP\/04058\/2020"]}]},{"name":"FCT\u2014Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>As intelligent systems become increasingly embedded in industrial ecosystems, the demand for transparency, reliability, and interpretability has intensified. This study investigates how explainable artificial intelligence (XAI) contributes to enhancing accountability, trust, and human\u2013machine collaboration across industrial contexts transitioning from Industry 4.0 to Industry 5.0. To achieve this objective, a systematic bibliometric literature review (LRSB) was conducted following the PRISMA framework, analysing 98 peer-reviewed publications indexed in Scopus. This methodological approach enabled the identification of major research trends, theoretical foundations, and technical strategies that shape the development and implementation of XAI within industrial settings. The findings reveal that explainability is evolving from a purely technical requirement to a multidimensional construct integrating ethical, social, and regulatory dimensions. Techniques such as counterfactual reasoning, causal modelling, and hybrid neuro-symbolic frameworks are shown to improve interpretability and trust while aligning AI systems with human-centric and legal principles, notably those outlined in the EU AI Act. The bibliometric analysis further highlights the increasing maturity of XAI research, with strong scholarly convergence around transparency, fairness, and collaborative intelligence. By reframing artificial intelligence through the lens of transparent machine reasoning, this study contributes to both theory and practice. It advances a conceptual model linking explainability with measurable indicators of trustworthiness and accountability, and it offers a roadmap for developing responsible, human-aligned AI systems in the era of Industry 5.0. Ultimately, the study underscores that fostering explainability not only enhances functional integrity but also strengthens the ethical and societal legitimacy of AI in industrial transformation.<\/jats:p>","DOI":"10.3390\/info16121044","type":"journal-article","created":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T08:13:49Z","timestamp":1764576829000},"page":"1044","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Illuminating Industry Evolution: Reframing Artificial Intelligence Through Transparent Machine Reasoning"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4793-4110","authenticated-orcid":false,"given":"Alb\u00e9rico Travassos","family":"Ros\u00e1rio","sequence":"first","affiliation":[{"name":"Instituto Polit\u00e9cnico de Set\u00fabal, Escola Superior de Ci\u00eancias Empresariais de Set\u00fabal, Campus do Instituto Polit\u00e9cnico de Set\u00fabal, Edif\u00edcio ESTS, Estefanilha, 2914-504 Set\u00fabal, Portugal"},{"name":"GOVCOPP\u2014Governance, Competitiveness and Public Policies, Campus Universit\u00e1rio de Santiago, Rua de S. Tiago DCSPT Room 12.3.8, 3810-193 Aveiro, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5900-2121","authenticated-orcid":false,"given":"Joana Carmo","family":"Dias","sequence":"additional","affiliation":[{"name":"Centro de Investiga\u00e7\u00e3o em Organiza\u00e7\u00f5es, Mercados e Gest\u00e3o Industrial (COMEGI), Universidade Lus\u00edada, 1349-001 Lisbon, Portugal"},{"name":"Faculdade de Economia, Universidade do Porto (FEP), R. Roberto Frias, 4200-464 Porto, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,12,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3333","DOI":"10.1007\/s11948-020-00276-4","article-title":"Towards transparency by design for artificial intelligence","volume":"26","author":"Felzmann","year":"2020","journal-title":"Sci. Eng. Ethics"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Greene, D., Hoffmann, A.L., and Stark, L. (2019, January 8\u201311). 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