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

Keng‐Boon Ooi(Fore School of Management), Garry Wei‐Han Tan(Adamson University), Mostafa Al‐Emran(British University in Dubai), Mohammed A. Al‐Sharafi(Universiti Tenaga Nasional), Alexandru Căpățînă("Dunarea de Jos" University of Galati), Amrita Chakraborty, Yogesh K. Dwivedi(Symbiosis International University), Tzu-Ling Huang(National Central University), Arpan Kumar Kar(Indian Institute of Technology Delhi), Voon‐Hsien Lee(Universiti Tunku Abdul Rahman), Xiu-Ming Loh(Universiti Tunku Abdul Rahman), Adrian Micu("Dunarea de Jos" University of Galati), Patrick Mikalef(SINTEF), Emmanuel Mogaji(Keele University), Neeraj Pandey(Indian Institute of Management Ahmedabad), Ramakrishnan Raman(Symbiosis International University), Nripendra P. Rana(Qatar University), Prianka Sarker(Manchester Metropolitan University), Anshuman Sharma(Ajman University), Ching‐I Teng(Chang Gung University), Samuel Fosso Wamba(TBS Education), Lai‐Wan Wong(Xiamen University Malaysia)
Journal of Computer Information Systems
October 5, 2023
Cited by 645

Abstract

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).


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