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

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
Subjects:	Bard ChatGPT Generative artificial intelligence large language model machine learning Human resource management Industrial research Music Language model Large language model Learning neural networks Machine-learning Organizational levels Smart phones Text images Machine learning
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id	my.uniten.dspace-34449
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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	13.222552

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

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