{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T04:27:52Z","timestamp":1778128072724,"version":"3.51.4"},"reference-count":74,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T00:00:00Z","timestamp":1763078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>As artificial intelligence (AI) technologies increasingly shape sustainability agendas, organizations face the strategic challenge of aligning AI-driven innovation with long-term environmental and social goals. While academic interest in this intersection is growing, research remains fragmented and often lacks actionable insights into the organizational capabilities needed to operationalize sustainable AI innovation. This study addresses this gap by exploring how knowledge-based organizational capabilities\u2014such as absorptive capacity, knowledge integration, organizational learning, and strategic leadership\u2014support the alignment of AI initiatives with sustainability strategies. Grounded in the knowledge-based view of the firm, we conduct a bibliometric and thematic analysis of 216 peer-reviewed articles to identify emerging conceptual domains at the nexus of AI, innovation, and sustainability. The analysis reveals five dominant capability clusters: (1) data governance and decision intelligence; (2) policy-driven innovation and green transitions; (3) digital transformation through education and innovation; (4) collaborative adoption for sustainable outcomes; and (5) AI for smart cities and climate action. These clusters illuminate the multi-dimensional roles that knowledge management and organizational capabilities play in enabling responsible, impactful, and context-sensitive AI adoption. In addition to mapping the intellectual structure of the field, the study proposes a set of strategic and policy-oriented recommendations for applying these capabilities in practice. The findings offer both theoretical contributions and practical guidance for firms, policymakers, and educators seeking to embed sustainability into AI-driven transformation. This work advances the discourse on innovation and knowledge management by providing a structured, capability-based perspective for designing and implementing sustainable AI strategies.<\/jats:p>","DOI":"10.3390\/info16110987","type":"journal-article","created":{"date-parts":[[2025,11,14]],"date-time":"2025-11-14T17:33:21Z","timestamp":1763141601000},"page":"987","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A Capability-Based Framework for Knowledge-Driven AI Innovation and Sustainability"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8741-0122","authenticated-orcid":false,"given":"M\u00e1rcia R. C.","family":"Santos","sequence":"first","affiliation":[{"name":"Intrepid Lab, Escola de Ci\u00eancias Econ\u00f3micas e das Organiza\u00e7\u00f5es, Universidade Lus\u00f3fona, 1749-024 Lisboa, Portugal"},{"name":"Centro de Estudos Transdisciplinares para o Desenvolvimento (CETRAD), Universidade de Tr\u00e1s-os-Montes e Alto Douro, 5000-660 Vila Real, Portugal"},{"name":"Business Research Unit (BRU-IUL), Instituto Universit\u00e1rio de Lisboa (ISCTE-IUL), 1649-026 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9804-7813","authenticated-orcid":false,"given":"Lu\u00edsa Cagica","family":"Carvalho","sequence":"additional","affiliation":[{"name":"Department of Economics and Management, School of Business and Administration, Instituto Polit\u00e9cnico de Set\u00fabal, 2910-761 Set\u00fabal, Portugal"},{"name":"Life Quality Research Centre (CIEQV), Instituto Polit\u00e9cnico de Set\u00fabal (IPS), Campus do IPS, 2810-583 Set\u00fabal, Portugal"}]},{"given":"Edgar","family":"Francisco","sequence":"additional","affiliation":[{"name":"School of Business and Administration, Instituto Polit\u00e9cnico de Set\u00fabal, 2910-761 Set\u00fabal, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1080\/10447318.2020.1741118","article-title":"Human-Centered Artificial Intelligence: Reliable, Safe & Trustworthy","volume":"36","author":"Shneiderman","year":"2020","journal-title":"Int. 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