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Professional training for effective adoption of Generative AI in the corporate world: bridging the gap

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datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
datacite.subject.sdg04:Educação de Qualidade
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
dc.contributor.authorGuedes, Fernando
dc.contributor.authorRocio, Vitor
dc.contributor.authorMartins, Paulo
dc.date.accessioned2026-01-06T11:26:46Z
dc.date.available2026-01-06T11:26:46Z
dc.date.issued2025
dc.description.abstractThis position paper emphasizes the critical role of professional training in facilitating the effective adoption of Generative AI (GenAI) in the corporate world. GenAI, with its ability to create new content from existing data, holds immense potential for transforming business processes, enhancing decision-making, and driving innovation. However, the adoption of GenAI faces significant challenges, including a shortage of skilled professionals, high implementation costs, data privacy concerns, and the complexity of integrating these technologies into existing systems. To address these challenges, this paper highlights the importance of comprehensive education and training programs tailored to equip employees with the necessary skills and knowledge. Such programs should focus on developing technical competencies and understanding the operational implications of GenAI. By analyzing current literature and case studies, this paper identifies key strategies for effective training and outlines best practices for integrating GenAI into corporate environments. The findings underscore the need for a strategic approach to training that aligns with the evolving demands of AI-driven innovation. This includes continuous learning and development initiatives, the promotion of a culture of innovation, and the implementation of responsible AI practices. By investing in professional training, organizations can bridge the skills gap, mitigate risks, and fully leverage the transformative potential of GenAI technologies, ultimately gaining a competitive edge in the market. Through this comprehensive exploration, the paper advocates for the integration of robust training frameworks that support the sustainable adoption of GenAI, ensuring that businesses are well-prepared to navigate the complexities and opportunities of the digital age.eng
dc.description.abstractEste position paper examina os desafios e oportunidades associados à adoção da Inteligência Artificial Generativa (IAG) no contexto empresarial, com um foco particular na vertente educacional. Utilizando uma abordagem abrangente e fundamentada em evidências empíricas, busca-se oferecer orientações valiosas para líderes empresariais e educacionais sobre a integração eficaz da IAG nas suas estratégias organizacionais e de ensino, visando preparar a força de trabalho do futuro. A implementação da IAG nas empresas enfrenta desafios significativos, incluindo a necessidade de capacitar colaboradores e superar barreiras culturais e organizacionais. Apenas 16% das empresas conseguiram implementar projetos de IA em escala, destacando a necessidade urgente de estratégias eficazes para a adoção da IAG (McKinsey & Company, 2022). A preparação adequada dos colaboradores é fundamental, e a educação corporativa desempenha um papel crucial nesse processo. As instituições de ensino também precisam adaptar-se rapidamente para fornecer as habilidades necessárias para trabalhar com a IAG, em colaboração com o setor empresarial (Autor & Dorn, 2013). A adoção bem-sucedida da IAG requer a aplicação de modelos de maturidade adaptados que considerem aspectos tecnológicos, organizacionais e educacionais. Empresas que utilizam tais modelos são 2,5 vezes mais propensas a obter resultados significativos (Harvard Business Review, 2019; Brynjolfsson & McAfee, 2014). É essencial que as instituições de ensino estejam alinhadas com esses modelos para garantir que os seus programas estejam em sintonia com as necessidades do mercado de trabalho. Além disso, é crucial adotar estratégias proativas e colaborativas entre empresas e instituições educacionais para transformar os desafios da IAG em oportunidades de crescimento e inovação. As empresas que adotam uma abordagem proativa para a IA são 2,7 vezes mais propensas a obter vantagem competitiva (Accenture, 2020; Schwab, 2016). Em suma, este position paper visa capacitar as organizações a abraçar o potencial transformador da IAG, com a educação como elemento central, promovendo um ecossistema de inovação sustentável para o século XXI.por
dc.identifier.citationGuedes, F., Rocio, V., Martins, P. (2025). Professional Training for Effective Adoption of Generative AI in the Corporate World: Bridging the Gap. In: Reis, A., et al. Technology and Innovation in Learning, Teaching and Education. TECH-EDU 2024. Communications in Computer and Information Science, vol 2481. Springer, Cham. https://doi.org/10.1007/978-3-032-02669-9_16
dc.identifier.doi10.1007/978-3-032-02669-9_16
dc.identifier.isbn9783032026682
dc.identifier.isbn9783032026699
dc.identifier.issn1865-0929
dc.identifier.issn1865-0937
dc.identifier.urihttp://hdl.handle.net/10400.2/20647
dc.language.isopor
dc.peerreviewedyes
dc.publisherSpringer Nature Switzerland
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-032-02669-9_16
dc.relation.ispartofCommunications in Computer and Information Science
dc.relation.ispartofTechnology and Innovation in Learning, Teaching and Education
dc.relation.ispartofseriesCommunications in Computer and Information Science
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.titleProfessional training for effective adoption of Generative AI in the corporate world: bridging the gapeng
dc.typeconference object
dspace.entity.typePublication
oaire.citation.endPage213
oaire.citation.startPage198
oaire.citation.titleTechnology and Innovation in Learning, Teaching and Education. TECH-EDU 2024
oaire.citation.volume2481
oaire.versionhttp://purl.org/coar/version/c_b1a7d7d4d402bcce
person.familyNameRocio
person.familyNameMartins
person.givenNameVitor
person.givenNamePaulo
person.identifierR-000-HKF
person.identifier.ciencia-id0418-C5A8-59E2
person.identifier.ciencia-idE614-2ECC-2D48
person.identifier.orcid0000-0002-3314-898X
person.identifier.orcid0000-0002-3040-9080
person.identifier.ridL-5119-2014
person.identifier.scopus-author-id24721665200
relation.isAuthorOfPublication7cab4248-456c-46bf-a1cf-bbd212928171
relation.isAuthorOfPublication56e28bd6-6b80-4b7e-b7ea-ffbe10b560be
relation.isAuthorOfPublication.latestForDiscovery7cab4248-456c-46bf-a1cf-bbd212928171

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