Exploring the Potential of ChatGPT in Diverse Industries: Applications and Research Challenges

Authors

  • Akbar Hussain Department of Artificial Intelligence, University of Management and Technology, Sialkot, Pakistan
  • Faiza Tahir Department of Artificial Intelligence, University of Management and Technology, Sialkot, Pakistan

Keywords:

Artificial Intelligence, ChatGPT, adoption and use, Pakistani industry, teaching and learning, Language Translation

Abstract

The rapid development of Artificial Intelligence (AI) has produced a conversational ChatGPT, an emerging tool that can be employed in several industries across the globe. In this paper, we study participants’ opinions about how the ChatGPT can be utilized positively in learning activities. A survey is conducted among 200 participants from a varied group of 30 firms including, educational institutions, software houses, healthcare sectors, and research & development (A&D) in order to analyse the perception and potential of ChatGPT in various industries in Pakistan. Additionally, we also acknowledge that the technology has several research challenges and future directions, such as the need for bias mitigation, stronger ethical frameworks, enhanced context awareness, and knowledge verification procedures. The findings indicate that a majority of the participants are acquainted with this tool; however, they do not consistently utilize it for their basic purposes. This study shows that ChatGPT can be helpful in learning activities, but emphasizes better guidelines to be provided for the participants in using this tool.

References

Gpt-4 technical report, 2023, [online] Available: https://cdn.openai.com/papers/gpt-4.pdf.

A. Radford, K. Narasimhan, T. Salimans and I. Sutskever, Improving language understanding by generative pre-training, 2018.

M. Khosla, A. Anand and V. Setty, "A comprehensive comparison of unsupervised network representation learning methods", arXiv preprint, 2019.

Q. Y. Sun, C. Q. Zhao, Y. Ju and F. Qian, "A survey on unsupervised domain adaptation in computer vision tasks", Sci. Sinica Technol., vol. 52, no. 1, pp. 26-54, 2022.

C. Ieracitano, A. Paviglianiti, M. Campolo, A. Hussain, E. Pasero and F. C. Morabito, "A novel automatic classification system based on hybrid unsupervised and supervised machine learning for electrospun nanofibers", IEEE/CAA J. Autom. Sinica, vol. 8, no. 1, pp. 64-76, Jan. 2021.

A. Radford, J. Wu, R. Child, D. Luan, D. Amodei and I. Sutskever, "Language models are unsupervised multitask learners", OpenAI Blog, vol. 1, no. 8, pp. 9, 2019.

Y. Zhang and Q. Yang, "A survey on multi-task learning", IEEE Trans. Knowl. Data Eng., vol. 34, no. 12, pp. 5586-5609, Dec. 2022.

T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, et al., "Language models are few-shot learners", Proc. 34th Int. Conf. Neural Information Processing Systems, pp. 1877-1901, 2020.

C. Finn, P. Abbeel and S. Levine, "Model-agnostic meta-learning for fast adaptation of deep networks", Proc. 34th Int. Conf. Machine Learning, pp. 1126-1135, 2017.

J. Beck, R. Vuorio, E. Z. Liu, Z. Xiong, L. Zintgraf, C. Finn, et al., "A survey of meta-reinforcement learning", arXiv preprint, 2023.

Q. X. Dong, L. Li, D. M. Dai, C. Zheng, Z. Y. Wu, B. B. Chang, et al., "A survey on in-context learning", arXiv preprint, 2022.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in neural information processing systems, 33, 1877-1901.

Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., & Smith, A. (2023). Generating scholarly content with ChatGPT: ethical challenges for medical publishing. The Lancet Digital Health, 5(3), e105-e106.

Adiguzel, T., Kaya, M. H., & Cansu, F. K. (2023). Revolutionizing education with AI: Exploring the transformative potential of ChatGPT. Contemporary Educational Technology, 15(3), ep429.

FIRAT, M. (2023). Integrating AI applications into learning management systems to enhance e-learning. Instructional Technology and Lifelong Learning, 4(1), 1-14.

Jiao, W., Wang, W., Huang, J. T., Wang, X., & Tu, Z. (2023). Is ChatGPT a good translator? A preliminary study. arXiv preprint arXiv:2301.08745.

Hariri, W. (2023). Unlocking the Potential of ChatGPT: A Comprehensive Exploration of its Applications, Advantages, Limitations, and Future Directions in Natural Language Processing. arXiv preprint arXiv:2304.02017.

Lin, Z., Cui, S., Li, G., Kang, X., Ji, F., Li, F., ... & Zhang, Y. (2021). Predict-Then-Decide: A Predictive Approach for Wait or Answer Task in Dialogue Systems. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29, 3012-3024.

Mufti?, F., Kaduni?, M., Mušinbegovi?, A., & Abd Almisreb, A. (2023). Exploring Medical Breakthroughs: A Systematic Review of ChatGPT Applications in Healthcare. Southeast Europe Journal of Soft Computing, 12(1), 13-41.

Curtis, N. (2023). To ChatGPT or not to ChatGPT? The impact of artificial intelligence on academic publishing. The Pediatric Infectious Disease Journal, 42(4), 275.

Kraugusteeliana, K., Indriana, I. H., Krisnanik, E., Muliawati, A., & Irmanda, H. N. (2023). Utilisation of ChatGPT's Artificcial Intelligence in Improving the Quality and Productivity of Lecturers' Work. Jurnal Pendidikan Dan Konseling (JPDK), 5(2), 3245-3249.

Gao, M., Ruan, J., Sun, R., Yin, X., Yang, S., & Wan, X. (2023). Human-like summarization evaluation with chatgpt. arXiv preprint arXiv:2304.02554.

Ray, P. P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121-154.

Zhou, J., Müller, H., Holzinger, A., & Chen, F. (2024). Ethical ChatGPT: Concerns, challenges, and commandments. Electronics, 13(17), 3417.

Stahl, B. C., & Eke, D. (2024). The ethics of ChatGPT–Exploring the ethical issues of an emerging technology. International Journal of Information Management, 74, 102700.

Jamali, A. S., Koondhar, M. Y., Depar, M. H., Maher, Z. A., & Memon, M. A Conceptual Framework For Smart Education System For Postgraduate Students.

Siddique, M. A. B., Asad, A., Rehman, A. U., Aslam, S., Asif, R. M., & Sadiq, M. T. (2020). Implementation of outcome-based education system in engineering education using real-time application

Bahrini, Aram, Mohammadsadra Khamoshifar, Hossein Abbasimehr, Robert J. Riggs, Maryam Esmaeili, Rastin Mastali Majdabadkohne, and Morteza Pasehvar. "ChatGPT: Applications, opportunities, and threats." In 2023 Systems and Information Engineering Design Symposium (SIEDS), pp. 274-279. IEEE, 2023.

Downloads

Published

2024-07-30 — Updated on 2025-12-26

Versions

How to Cite

Hussain, A., & Faiza Tahir. (2025). Exploring the Potential of ChatGPT in Diverse Industries: Applications and Research Challenges. University of Sindh Journal of Information and Communication Technology, 8(1), 12–18. Retrieved from https://sujo.usindh.edu.pk/index.php/USJICT/article/view/7030 (Original work published July 30, 2024)

Most read articles by the same author(s)

Obs.: This plugin requires at least one statistics/report plugin to be enabled. If your statistics plugins provide more than one metric then please also select a main metric on the admin's site settings page and/or on the journal manager's settings pages.