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The advent of Artificial Intelligence (AI) however reverts this paradigm in the context of Industry 5.0. The focus is moving from \u201chow innovation fosters AI\u201d to \u201chow AI fosters innovation\u201d. Therefore, our research question can be stated as follows: What factors influence the effect of AI on Innovation Capacity in the context of Industry 5.0? To address this question we conduct a scoping review of a vast body of literature spanning engineering, human sciences, and management science. We conduct a keyword-based literature search completed by bibliographic analysis, then classify the resulting 333 works into 3 classes and 15 clusters which we critically analyze. We extract 3 hypotheses setting associations between 4 factors: company age, AI maturity, manufacturing strategy, and innovation capacity. The review uncovers several debates and research gaps left unsolved by the existing literature. In particular, it raises the debate whether the Industry5.0 promise can be achieved while Artificial General Intelligence (AGI) remains out of reach. It explores diverging possible futures driven toward social manufacturing or mass customization. Finally, it discusses alternative AI policies and their incidence on open and internal innovation. We conclude that the effect of AI on innovation capacity can be synergic, deceptive, or substitutive depending on the alignment of the uncovered factors. Moreover, we identify a set of 12 indicators enabling us to measure these factors to predict AI\u2019s effect on innovation capacity. These findings provide researchers with a new understanding of the interplay between artificial intelligence and human intelligence. They provide practitioners with decision metrics for a successful transition to Industry 5.0.<\/jats:p>","DOI":"10.1007\/s10462-024-10864-6","type":"journal-article","created":{"date-parts":[[2024,7,26]],"date-time":"2024-07-26T18:01:56Z","timestamp":1722016916000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["AI\u2019s effect on innovation capacity in the context of industry 5.0: a scoping review"],"prefix":"10.1007","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9328-9581","authenticated-orcid":false,"given":"Adrien","family":"B\u00e9cue","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3357-1195","authenticated-orcid":false,"given":"Joao","family":"Gama","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2672-5950","authenticated-orcid":false,"given":"Pedro Quelhas","family":"Brito","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,7,26]]},"reference":[{"issue":"6","key":"10864_CR1","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1257\/aer.20160696","volume":"108","author":"D Acemoglu","year":"2018","unstructured":"Acemoglu D, Restrepo P (2018) The race between machine and man: implications of technology for growth, factor shares and employment. 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