The Role of Generative AI and Digital Transformation in Modernizing Performance Management Processes: Goal Setting
DOI:
https://doi.org/10.32628/CSEIT251112236Keywords:
Digital Transformation, Performance Management Systems (PMS), artificial intelligence (AI), Automation, Goal Setting, Performance Tracking, Compensation ManagementAbstract
Artificial Intelligence and digital transformation have revolutionized traditional business operations, resulting in enhanced performance management systems. Performance management systems are frequently perceived as fundamental compliance initiatives. However, the efficacy of a performance management system can significantly contribute to human resource capital investment and cost reduction. It is important to invest in an effective performance management system that can enable continuous monitoring of employee engagement and attrition risk. This study aims to provide an analysis of how Artificial Intelligence (AI) and AI-based products can drive efficiency within the performance management process. Performance management systems can improve transparency, reduce bias and provide insights for managers leading to improved decision-making. The necessity to replace legacy systems with contemporary AI-driven performance management systems benefits organizations both operationally and strategically.
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Bilgram, V., & Laarmann, F. (2023). Accelerating Innovation With Generative AI: AI-Augmented Digital Prototyping and Innovation Methods. IEEE Engineering Management Review, 51(2), 18–25. https://doi.org/10.1109/emr.2023.3272799
Narayanan, V. (2023). The transformative AI initiative: from process digitization to AI strategic digitalization. Strategy & Leadership, 51(2), 24–30. https://doi.org/10.1108/sl-01-2023-0009
Ninduwezuor-Ehiobu, N., Egbokhaebho, B., Tula, O., Banso, A., Daraojimba, C., Gidiagba, J., Ogunjobi, O., & Ofonagoro, K. (2023). TRACING THE EVOLUTION OF AI AND MACHINE LEARNING APPLICATIONS IN ADVANCING MATERIALS DISCOVERY AND PRODUCTION PROCESSES. Engineering Science & Technology Journal, 4(3), 66–83. https://doi.org/10.51594/estj.v4i3.552
Park, H. E. (Grace). (2024). The double‐edged sword of generative artificial intelligence in digitalization: An affordances and constraints perspective. Psychology & Marketing, 41(11), 2924–2941. https://doi.org/10.1002/mar.22094
Patil, D., Rane, N. L., & Rane, J. (2024). Applications of ChatGPT and generative artificial intelligence in transforming the future of various business sectors. deep science. https://doi.org/10.70593/978-81-981367-8-7_1
Prasad Agrawal, K. (2023). Organizational Sustainability of Generative AI-Driven Optimization Intelligence. Journal of Computer Information Systems, ahead-of-print(ahead-of-print), 1–15. https://doi.org/10.1080/08874417.2023.2286540
Rane, N. (2024). Role and challenges of ChatGPT, Gemini, and similar generative artificial intelligence in human resource management. Studies in Economics and Business Relations, 5(1), 11–23. https://doi.org/10.48185/sebr.v5i1.1001
Lee, K. (2022). Machine learning applications in compensation management. Data Insights Review, 10(4), 100-120.
Madhumita, R., & Das, P. (2022). AI-driven employee performance management systems: Opportunities and challenges. International Journal of Business Analytics, 9(3), 45-60. https://doi.org/10.4018/IJBA.20220301
Kirov, V., & Malamin, B. (2022). Are Translators Afraid of Artificial Intelligence? Societies, 12(2), 70. https://doi.org/10.3390/soc12020070
Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2019). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022
Zhang, C., Zhu, W., Dai, J., Wu, Y., & Chen, X. (2023). Ethical impact of artificial intelligence in managerial accounting. International Journal of Accounting Information Systems, 49, 100619. https://doi.org/10.1016/j.accinf.2023.100619
Deloitte Insights. (2023). The impact of AI on goal setting and performance management. Retrieved from https://www2.deloitte.com/content/dam/Deloitte/us/Documents/consulting/us-state-of-gen-ai-q3.pdf
McKinsey & Company. (2023). AI in workforce compensation: Trends and insights. Retrieved from https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america
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