The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions

In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet...

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Main Authors: Ooi K.-B., Tan G.W.-H., Al-Emran M., Al-Sharafi M.A., Capatina A., Chakraborty A., Dwivedi Y.K., Huang T.-L., Kar A.K., Lee V.-H., Loh X.-M., Micu A., Mikalef P., Mogaji E., Pandey N., Raman R., Rana N.P., Sarker P., Sharma A., Teng C.-I., Wamba S.F., Wong L.-W.
Other Authors: 14619509700
Format: Article
Published: Taylor and Francis Ltd. 2024
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spelling my.uniten.dspace-344492024-10-14T11:19:52Z The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions Ooi K.-B. Tan G.W.-H. Al-Emran M. Al-Sharafi M.A. Capatina A. Chakraborty A. Dwivedi Y.K. Huang T.-L. Kar A.K. Lee V.-H. Loh X.-M. Micu A. Mikalef P. Mogaji E. Pandey N. Raman R. Rana N.P. Sarker P. Sharma A. Teng C.-I. Wamba S.F. Wong L.-W. 14619509700 57035671700 56593108000 57196477711 35209737400 57208560088 35239818900 57203386123 55911169300 42061780600 57212302322 58355484100 42761793700 56823605700 57813546700 55808097300 50262828700 57211180165 57222817448 14623453000 14833520200 57195363118 Bard ChatGPT Generative artificial intelligence large language model machine learning Human resource management Industrial research Music Bard ChatGPT Generative artificial intelligence Language model Large language model Learning neural networks Machine-learning Organizational levels Smart phones Text images Machine learning In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management). � 2023 International Association for Computer Information Systems. Article in press 2024-10-14T03:19:52Z 2024-10-14T03:19:52Z 2023 Article 10.1080/08874417.2023.2261010 2-s2.0-85173499156 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173499156&doi=10.1080%2f08874417.2023.2261010&partnerID=40&md5=71d660d872498623c020fe6a8f42a6d7 https://irepository.uniten.edu.my/handle/123456789/34449 Taylor and Francis Ltd. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Bard
ChatGPT
Generative artificial intelligence
large language model
machine learning
Human resource management
Industrial research
Music
Bard
ChatGPT
Generative artificial intelligence
Language model
Large language model
Learning neural networks
Machine-learning
Organizational levels
Smart phones
Text images
Machine learning
spellingShingle Bard
ChatGPT
Generative artificial intelligence
large language model
machine learning
Human resource management
Industrial research
Music
Bard
ChatGPT
Generative artificial intelligence
Language model
Large language model
Learning neural networks
Machine-learning
Organizational levels
Smart phones
Text images
Machine learning
Ooi K.-B.
Tan G.W.-H.
Al-Emran M.
Al-Sharafi M.A.
Capatina A.
Chakraborty A.
Dwivedi Y.K.
Huang T.-L.
Kar A.K.
Lee V.-H.
Loh X.-M.
Micu A.
Mikalef P.
Mogaji E.
Pandey N.
Raman R.
Rana N.P.
Sarker P.
Sharma A.
Teng C.-I.
Wamba S.F.
Wong L.-W.
The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
description In a short span of time since its introduction, generative artificial intelligence (AI) has garnered much interest at both personal and organizational levels. This is because of its potential to cause drastic and widespread shifts in many aspects of life that are comparable to those of the Internet and smartphones. More specifically, generative AI utilizes machine learning, neural networks, and other techniques to generate new content (e.g. text, images, music) by analyzing patterns and information from the training data. This has enabled generative AI to have a wide range of applications, from creating personalized content to improving business operations. Despite its many benefits, there are also significant concerns about the negative implications of generative AI. In view of this, the current article brings together experts in a variety of fields to expound and provide multi-disciplinary insights on the opportunities, challenges, and research agendas of generative AI in specific industries (i.e. marketing, healthcare, human resource, education, banking, retailing, the workplace, manufacturing, and sustainable IT management). � 2023 International Association for Computer Information Systems.
author2 14619509700
author_facet 14619509700
Ooi K.-B.
Tan G.W.-H.
Al-Emran M.
Al-Sharafi M.A.
Capatina A.
Chakraborty A.
Dwivedi Y.K.
Huang T.-L.
Kar A.K.
Lee V.-H.
Loh X.-M.
Micu A.
Mikalef P.
Mogaji E.
Pandey N.
Raman R.
Rana N.P.
Sarker P.
Sharma A.
Teng C.-I.
Wamba S.F.
Wong L.-W.
format Article
author Ooi K.-B.
Tan G.W.-H.
Al-Emran M.
Al-Sharafi M.A.
Capatina A.
Chakraborty A.
Dwivedi Y.K.
Huang T.-L.
Kar A.K.
Lee V.-H.
Loh X.-M.
Micu A.
Mikalef P.
Mogaji E.
Pandey N.
Raman R.
Rana N.P.
Sarker P.
Sharma A.
Teng C.-I.
Wamba S.F.
Wong L.-W.
author_sort Ooi K.-B.
title The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
title_short The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
title_full The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
title_fullStr The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
title_full_unstemmed The Potential of Generative Artificial Intelligence Across Disciplines: Perspectives and Future Directions
title_sort potential of generative artificial intelligence across disciplines: perspectives and future directions
publisher Taylor and Francis Ltd.
publishDate 2024
_version_ 1814061056997195776
score 13.214268