CHATGPT INFLUENCE IN WORK ENVIRONMENT OF IT COMPANIES IN MACEDONIA

Authors

  • Leonid Djinevski University of Skopje, Skopje, North Macedonia

Keywords:

ChatGPT, AI, workflow

Abstract

The rapid integration of advanced artificial intelligence technologies is revolutionizing various industries, with the Information Technology field being at the forefront of this transformation. This paper examines the influence of ChatGPT, a state-of-the-art language model developed by OpenAI, on the work environment of IT companies in Macedonia. ChatGPT's applications in automating routine tasks, enhancing customer support, assisting with coding and debugging, and managing knowledge significantly boost productivity and foster innovation. By providing real-time solutions and improving communication, ChatGPT supports a more efficient and collaborative work environment.
To gain a deeper understanding of ChatGPT's impact, we conducted a comprehensive survey involving three IT companies in Macedonia. The survey explored the extent of ChatGPT's adoption, its perceived benefits, and the challenges encountered during its integration. The findings reveal that ChatGPT has been instrumental in automating repetitive tasks, thereby allowing employees to focus on strategic and creative endeavors. Furthermore, it has improved customer satisfaction by providing timely and accurate support.
However, the deployment of ChatGPT also presents challenges, including ethical considerations, integration complexities, and the need for employee adaptation. Through detailed analysis and case studies of the surveyed companies, this paper highlights the practical benefits and potential obstacles of integrating ChatGPT into existing workflows. The results underscore ChatGPT's transformative potential in enhancing operational efficiency and driving innovation while emphasizing the importance of addressing ethical and practical implementation challenges. This study provides valuable insights for IT companies considering the adoption of AI technologies like ChatGPT in their work environments.

References

Ding, X., Chen, L., Emani, M., Liao, C., Lin, P. H., Vanderbruggen, T., & Du, W. (2023, November). Hpc-gpt: Integrating large language model for high-performance computing. In Proceedings of the SC'23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysis (pp. 951-960). Kang, Y., Cai, Z., Tan, C. W., Huang, Q., & Liu, H. (2020). Natural language processing (NLP) in management research: A literature review. Journal of Management Analytics, 7(2), 139-172. Menghani, G. (2023). Efficient deep learning: A survey on making deep learning models smaller, faster, and better. ACM Computing Surveys, 55(12), 1-37. Nilsson, N. J. (2009). The quest for artificial intelligence. Cambridge University Press. Raj, R., Singh, A., Kumar, V., & Verma, P. (2023). Analyzing the potential benefits and use cases of ChatGPT as a tool for improving the efficiency and effectiveness of business operations. BenchCouncil Transactions on Benchmarks, Standards and Evaluations, 3(3), 100140. Roumeliotis, K. I., & Tselikas, N. D. (2023). Chatgpt and open-ai models: A preliminary review. Future Internet, 15(6), 192. Wang, D. Q., Feng, L. Y., Ye, J. G., Zou, J. G., & Zheng, Y. F. (2023). Accelerating the integration of ChatGPT and other large‐scale AI models into biomedical research and healthcare. MedComm–Future Medicine, 2(2), e43. Wu, T., He, S., Liu, J., Sun, S., Liu, K., Han, Q. L., & Tang, Y. (2023). A brief overview of ChatGPT: The history, status quo and potential future development. IEEE/CAA Journal of Automatica Sinica, 10(5), 1122-1136. Yenduri, G., Ramalingam, M., Selvi, G. C., Supriya, Y., Srivastava, G., Maddikunta, P. K. R., ... & Gadekallu, T. R. (2024). Gpt (generative pre-trained transformer)–a comprehensive review on enabling technologies, potential applications, emerging challenges, and future directions. IEEE Access. Zhang, C., & Lu, Y. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, 23, 100224.

Downloads

Published

2024-08-17

How to Cite

Djinevski, L. (2024). CHATGPT INFLUENCE IN WORK ENVIRONMENT OF IT COMPANIES IN MACEDONIA. KNOWLEDGE - International Journal , 65(3), 285–288. Retrieved from https://ojs.ikm.mk/index.php/kij/article/view/6926