The digital revolution: impacts of digital transformation and ai on health, education, and the economy in Brazil
DOI:
https://doi.org/10.5585/2024.27640Keywords:
digital transformation, artificial intelligence, health, education, economy.Abstract
Objective of the study: This article analyzes how Digital Transformation (DT) and Artificial Intelligence (AI) are impacting the health, education, and economy sectors in Brazil through process optimization and improved efficiency in essential services.
Originality/Relevance: The analysis provides concrete data and examples of how DT and AI are driving innovation and digital inclusion in Brazil.
Social/Management contributions: Challenges in governance and the need for greater investment in digital infrastructure and regulation are discussed.
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References
Bilgram, V., & Laarmann, F. (2023). Accelerating innovation with generative AI: AI-augmented digital prototyping and innovation methods. IEEE Engineering Management Review, 51(1), 18-25. https://doi.org/10.1109/EMR.2023.3272799
Brasil. Ministério da Saúde. Secretaria-Executiva. Departamento de Informática do SUS. (2020). Estratégia de Saúde Digital para o Brasil 2020-2028. Ministério da Saúde. https://bvsms.saude.gov.br/bvs/publicacoes/estrategia_saude_digital_Brasil.pdf
Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W.W. Norton & Company.
Cahyo, L. M., & Astuti, S. D. (2023). Early detection of health problems through artificial intelligence (ai) technology in hospital information management: A literature review study. Journal of Medical and Health Studies, 4(3), 37-42.
CGEE - Centro de Gestão e Estudos Estratégicos. (2024). Benchmarking de indicadores de inteligência artificial: Série Documentos Técnicos. Brasília: CGEE.
Cramarenco, R., Burcă-Voicu, M. I., & Dabija, D. C. (2023). The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review. Oeconomia Copernicana. https://doi.org/10.24136/oc.2023.022
Deloitte & FEBRABAN. (2024). Pesquisa FEBRABAN de tecnologia bancária 2024. https://www.deloitte.com/br/pt/Industries/financial-services/research/pesquisa-febraban-tecnologia-bancaria.html
Governo do Brasil. (2024). Escolas conectadas completa um ano promovendo cidadania digital. Ministério da Educação. https://www.gov.br/mec/pt-br/assuntos/noticias/2024/setembro/escolas-conectadas-completa-um-ano-promovendo-cidadania-digital
Innovation Intelligence. (2024). Generative AI and the future of work & education. Innovation Intelligence.
Maslej, N., Fattorini, L., Perrault, R., Parli, V., Reuel, A., Brynjolfsson, E., Etchemendy, J., Ligett, K., Lyons, T., Manyika, J., Niebles, J. C.,
Shoham, Y., & Clark, J. (2024). The AI Index 2024 Annual Report. AI Index Steering Committee, Institute for Human-Centered AI, Stanford
University.
Ministério da Ciência, Tecnologia e Inovações. (2021). Estratégia Brasileira de Inteligência Artificial (EBIA). Brasília: Ministério da Ciência, Tecnologia e Inovações.
Ministério da Saúde. (2024). Meu SUS Digital. Ministério da Saúde
Valor Econômico & PwC Brasil. (2024). Valor Inovação Brasil 2024. Valor Econômico S.A.
Vasconcellos, J., Barra, H., Ernanny, M., Telles, G., Martins, A., Pencz, M., & Ramos, V. (2023). Latin America Digital Transformation Report 2023. Atlantico Venture Partners.
Vial, G. (2019). Understanding digital transformation: A review and a research agenda. Journal of Strategic Information Systems, 28(2), 118-144. https://doi.org/10.1016/j.jsis.2019.01.003
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Dong, J. Q., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889-901. https://doi.org/10.1016/j.jbusres.2019.09.022
Standen, P., Brown, D., Taheri, M., Galvez Trigo, M. J., Boulton, H., Burton, A., Hallewell, M., Lathe, J. G., Shopland, N., Blanco Gonzalez, M. A., Kwiatkowska, G., Milli, E., Cobello, S., Mazzucato, A., & Traversi, M. (2020). An evaluation of an adaptive learning system based on multimodal affect recognition for learners with intellectual disabilities. British Journal of Educational Technology, 51(5), 1748–1765. https://doi.org/10.1111/bjet.13010
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Copyright (c) 2024 Adiemir Hortega Medeiros, Priscila Rezende da Costa, Benny Kramer Costa, Luís Fábio Cavalcanti da Silva
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