Unveiling the potential of generative artificial intelligence: a multidimensional journey into the future
Purpose The launch of ChatGPT has brought the large language model (LLM)-based generative artificial intelligence (GAI) into the spotlight, triggering the interests of various stakeholders to seize the possible opportunities implicated by it. Nevertheless, there are also challenges that the stakeholders should observe when they are considering the potential of GAI. Given this backdrop, this study presents the viewpoints gathered from various subject experts on six identified areas. Design/methodology/approach Through an expert-based approach, this paper gathers the viewpoints of various subject experts on the identified areas of tourism and hospitality, marketing, retailing, service operations, manufacturing and healthcare. Findings The subject experts first share an overview of the use of GAI, followed by the relevant opportunities and challenges in implementing GAI in each identified area. Afterwards, based on the opportunities and challenges, the subject experts propose several research agendas for the stakeholders to consider. Originality/value This paper serves as a frontier in exploring the opportunities and challenges implicated by the GAI in six identified areas that this emerging technology would considerably influence. It is believed that the viewpoints offered by the subject experts would enlighten the stakeholders in the identified areas.
Authors
- Keng‐Boon Ooi (ORCID: https://orcid.org/0000-0002-3384-1207)
- Lai‐Wan Wong (ORCID: https://orcid.org/0000-0003-1961-8452)
- Charles Dennis (ORCID: https://orcid.org/0000-0001-8793-4823)
- Μαριάννα Σιγάλα (ORCID: https://orcid.org/0000-0001-8997-2292)
- Alex Koohang (ORCID: https://orcid.org/0000-0002-4565-0408)
- Cihan Çobanoğlu (ORCID: https://orcid.org/0000-0001-9556-6223)
- Tat‐Huei Cham (ORCID: https://orcid.org/0000-0001-7636-5928)
- Yogesh Kumar Dwivedi (ORCID: https://orcid.org/0000-0002-5547-9990)
- Garry Wei‐Han Tan (ORCID: https://orcid.org/0000-0003-2974-2270)
- Yun-Chia Tang
- Anubhav Mishra (ORCID: https://orcid.org/0000-0001-7412-2666)
- Eugene Cheng‐Xi Aw (ORCID: https://orcid.org/0000-0001-6712-1171)
- Ramakrishnan Raman (ORCID: https://orcid.org/0000-0003-3642-6989)
- Laurie Hughes (ORCID: https://orcid.org/0000-0002-0956-0608)
- Ian Phau (ORCID: https://orcid.org/0000-0002-0759-6092)
- Chieh‐Yu Lin (ORCID: https://orcid.org/0000-0003-3393-9674)
- Heather Linton Kelly
- Jun-Jie Hew
Institutions
- Edith Cowan University (AU)
- Tunghai University (TW)
- Georgia State University (US)
- Curtin University (AU)
- Symbiosis International University (IN)
- University of South Florida (US)
- Jaipuria Institute of Management (IN)
- Swansea University (GB)
- Xiamen University Malaysia (MY)
- UCSI University (MY)
- Middlesex University London (GB)
- University of Newcastle Australia (AU)
- Chang Jung Christian University (TW)
- Universiti Tunku Abdul Rahman (MY)
- Middle Georgia State University (US)
Publication Details
- Journal
- Industrial Management & Data Systems
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1108/imds-10-2023-0703
- Citations
- 15
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.80