<?xml version="1.0"?><rdf:RDF xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:edm="http://www.europeana.eu/schemas/edm/" xmlns:wgs84_pos="http://www.w3.org/2003/01/geo/wgs84_pos" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:rdaGr2="http://rdvocab.info/ElementsGr2" xmlns:oai="http://www.openarchives.org/OAI/2.0/" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:ore="http://www.openarchives.org/ore/terms/" xmlns:skos="http://www.w3.org/2004/02/skos/core#" xmlns:dcterms="http://purl.org/dc/terms/"><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:doc-WBRGE57Z/e99766a1-4c20-4acb-81e0-df49cf8e7a21/PDF"><dcterms:extent>599 KB</dcterms:extent></edm:WebResource><edm:WebResource rdf:about="http://www.dlib.si/stream/URN:NBN:SI:doc-WBRGE57Z/3a251a80-7930-42e3-9e55-57a4c251a2dd/TEXT"><dcterms:extent>0 KB</dcterms:extent></edm:WebResource><edm:ProvidedCHO rdf:about="URN:NBN:SI:doc-WBRGE57Z"><dcterms:issued>2025</dcterms:issued><dc:creator>Garlatti Costa, Grazia</dc:creator><dc:creator>Pugliese, Roberto</dc:creator><dc:creator>Venier, Francesco</dc:creator><dc:format xml:lang="sl">številka:1</dc:format><dc:format xml:lang="sl">letnik:23</dc:format><dc:format xml:lang="sl">str. 79-111, 114-115</dc:format><dc:identifier>DOI:10.26493/1854-6935.23.79-111</dc:identifier><dc:identifier>ISSN:1854-6935</dc:identifier><dc:identifier>COBISSID_HOST:281129731</dc:identifier><dc:identifier>URN:URN:NBN:SI:doc-WBRGE57Z</dc:identifier><dc:language>en</dc:language><dc:publisher xml:lang="sl">University of Primorska Press</dc:publisher><dc:source xml:lang="sl">Managing global transitions</dc:source><dc:subject xml:lang="en">artificial intelligence</dc:subject><dc:subject xml:lang="en">diffusion of innovations theory</dc:subject><dc:subject xml:lang="en">early adopters</dc:subject><dc:subject xml:lang="en">implementation challenges</dc:subject><dc:subject xml:lang="en">Italian companies</dc:subject><dc:subject xml:lang="sl">italijanska podjetja</dc:subject><dc:subject xml:lang="sl">izzivi implementacije</dc:subject><dc:subject xml:lang="sl">teorija difuzije inovacij</dc:subject><dc:subject xml:lang="sl">umetna inteligenca</dc:subject><dc:subject xml:lang="sl">zgodnji uporabniki</dc:subject><dc:title xml:lang="sl">Unveiling organizational AI adoption patterns in Italian companies through the lens of the diffusion of innovations theory|</dc:title><dc:description xml:lang="sl">This paper investigates the adoption and integration of artificial intelligence (AI) technologies within a sample of 237 Italian enterprises using the Diffusion of Innovations (DOI) theory as the theoretical framework. It examines the characteristics of companies leading in AI adoption, evaluating their alignment with the innovator and early adopter profiles defined by Everett Rogers in 2003 within the DOI framework. The research emphasizes AI’s significant role in enhancing operational efficiency, fostering innovation, securing competitive advantage, and driving long-term growth. It also identifies challenges such as lack of skills, data management issues, and ethical concerns. Our findings contribute empirical evidence to the academic literature on the DOI theory, addressing the underexplored context of AI in Italy. The study provides a nuanced perspective on AI’s impact on employment and sets a foundation for future research, offering managerial insights for strategically deploying AI</dc:description><dc:description xml:lang="sl">Ta prispevek raziskuje sprejemanje in integracijo tehnologij umetne inteligence (AI) v vzorcu 237 italijanskih podjetij, pri čemer uporablja teorijo difuzije inovacij (Diffusion of Innovations – DOI) kot teoretični okvir. Proučuje značilnosti podjetij, ki so vodilna pri sprejemanju AI, in ocenjuje njihovo usklajenost s profili inovatorjev in zgodnjih sprejemnikov, ki jih je Everett Rogers opredelil leta 2003 v okviru DOI. Raziskava poudarja pomembno vlogo umetne inteligence pri povečevanju operativne učinkovitosti, spodbujanju inovacij, zagotavljanju konkurenčne prednosti in spodbujanju dolgoročne rasti. Opredeljuje tudi izzive, kot so pomanjkanje veščin, težave z upravljanjem podatkov in etični pomisleki. Naše ugotovitve prispevajo empirične dokaze k akademski literaturi o teoriji DOI in obravnavajo premalo raziskan kontekst umetne inteligence v Italiji. Študija ponuja niansiran pogled na vpliv AI na zaposlovanje in postavlja temelje za prihodnje raziskave, pri čemer ponuja vodstvene vpoglede za strateško uvajanje AI</dc:description><edm:type>TEXT</edm:type><dc:type xml:lang="sl">znanstveno časopisje</dc:type><dc:type xml:lang="en">journals</dc:type><dc:type rdf:resource="http://www.wikidata.org/entity/Q361785" /></edm:ProvidedCHO><ore:Aggregation rdf:about="http://www.dlib.si/?URN=URN:NBN:SI:doc-WBRGE57Z"><edm:aggregatedCHO rdf:resource="URN:NBN:SI:doc-WBRGE57Z" /><edm:isShownBy rdf:resource="http://www.dlib.si/stream/URN:NBN:SI:doc-WBRGE57Z/e99766a1-4c20-4acb-81e0-df49cf8e7a21/PDF" /><edm:rights rdf:resource="http://creativecommons.org/licenses/by-sa/4.0/" /><edm:provider>Slovenian National E-content Aggregator</edm:provider><edm:intermediateProvider xml:lang="en">National and University Library of Slovenia</edm:intermediateProvider><edm:dataProvider xml:lang="sl">Univerza na Primorskem, Fakulteta za management</edm:dataProvider><edm:object rdf:resource="http://www.dlib.si/streamdb/URN:NBN:SI:doc-WBRGE57Z/maxi/edm" /><edm:isShownAt rdf:resource="http://www.dlib.si/details/URN:NBN:SI:doc-WBRGE57Z" /></ore:Aggregation></rdf:RDF>