Huňady, Ján2025-08-122025-08-1220252787-2572https://doi.org/10.31181/jdaic10023062025hhttps://repo.umb.sk/handle/123456789/759In: Journal of decision analytics and intelligent computing. Belehrad : Scientific oasis, 2025. ISSN 2787-2572. Vol. 5, no. 1 (2025), pp. 99-110.This paper empirically examines factors and firm-level determinants of artificial intelligence (AI) adoption. It is particularly focused on factors related to missing skills in European small and medium-sized enterprises (SMEs). It uses micro-level data from Flash Eurobarometer 537, which includes more than 19,000 firms from 27 EU and 9 non-EU countries. The aim was to identify the key characteristics associated with the likelihood of AI adoption and the anticipation of significant skill transformations related to AI adoption. Results of probit and bivariate probit regressions reveal that firms with younger employees, growing turnover, and membership in industry clusters are more likely to adopt AI. Moreover, firms that have problems with shortages of skills in specific areas (such as IT, R&D, marketing, and customer care) are more likely to adopt AI. These firms also expect that AI adoption will significantly change their skill demands in the future. Interestingly, community size and difficulties with recruiting are closely related to the adoption of AI but have limited effect on firms' expectations on its impact on skills demanded in the future. Furthermore, the analysis revealed significant differences across industries. These findings contribute to the emerging literature on digital transformation and expand the knowledge on the decision-making process for AI introduction by clarifying the drivers of AI adoption and its perceived skill implications.enCC BY Creative Commons Attribution 4.0. Internationalinfo:eu-repo/semantics/openAccessumelá inteligenciaartificial intelligencezručnostiabilitiesmalé a stredné podnikymalé a stredné podniky (MaSP)small and medium-sized enterprisessmall and medium-sized companiessmall and medium enterprisesSMEsDrivers of AI adoption in SMEs: Missing skills and other firm-level factorsArticle