TY - JOUR
T1 - The Potential of Generative Artificial Intelligence Across Disciplines
T2 - Perspectives and Future Directions
AU - Ooi, Keng Boon
AU - Tan, Garry Wei Han
AU - Al-Emran, Mostafa
AU - Al-Sharafi, Mohammed A.
AU - Capatina, Alexandru
AU - Chakraborty, Amrita
AU - Dwivedi, Yogesh K.
AU - Huang, Tzu Ling
AU - Kar, Arpan Kumar
AU - Lee, Voon Hsien
AU - Loh, Xiu Ming
AU - Micu, Adrian
AU - Mikalef, Patrick
AU - Mogaji, Emmanuel
AU - Pandey, Neeraj
AU - Raman, Ramakrishnan
AU - Rana, Nripendra P.
AU - Sarker, Prianka
AU - Sharma, Anshuman
AU - Teng, Ching I.
AU - Wamba, Samuel Fosso
AU - Wong, Lai Wan
N1 - Publisher Copyright:
© 2023 International Association for Computer Information Systems.
PY - 2023
Y1 - 2023
N2 - 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).
AB - 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).
KW - Bard
KW - ChatGPT
KW - Generative artificial intelligence
KW - large language model
KW - machine learning
UR - http://www.scopus.com/inward/record.url?scp=85173499156&partnerID=8YFLogxK
U2 - 10.1080/08874417.2023.2261010
DO - 10.1080/08874417.2023.2261010
M3 - 期刊論文
AN - SCOPUS:85173499156
SN - 0887-4417
JO - Journal of Computer Information Systems
JF - Journal of Computer Information Systems
ER -