AI-Powered Performance Management: A Case Study in Accra

Authors

Samuel Asante

School of Business and Economics, Universiti Putra Malaysia, Serdang (Malaysia)

Article Information

DOI: 10.51244/IJRSI.2025.1210000337

Subject Category: Artificial Intelligence

Volume/Issue: 12/10 | Page No: 3919-3923

Publication Timeline

Submitted: 2025-11-12

Accepted: 2025-11-18

Published: 2025-11-22

Abstract

Artificial Intelligence (AI) is revolutionizing the management of organizations around the globe and how employee performance is measured and improved. The study investigated the use and effect of AI-powered performance management systems in selected firms in Accra, Ghana. By employing a mixed-methods methodology, data were gathered from 120 employees and managers across multiple sectors, including banking, telecommunications, and technology. Results indicate that AI tools facilitate transparency, objectivity, and efficiency in the performance assessment processes. Nevertheless, challenges to implementation such as high costs, shortage of technical know-how, and data privacy concerns remain. The study argues that by augmenting AI with human supervision and ethical frameworks, AI can support strategic human resource development and organizational excellence. Recommendations include capacity building, regulatory policy development, and adoption of hybrid appraisal models.

Keywords

Artificial Intelligence, Performance Management

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References

1. Akinola, A. (2022). Artificial intelligence adoption and human resource management practices in Nigerian firms. African Journal of Management Research, 28(2), 45–61. [Google Scholar] [Crossref]

2. Asare, K., & Ofori, D. (2022). Digital transformation and organizational effectiveness in emerging markets: Evidence from Ghana’s service sector. Journal of African Business, 23(4), 612–629. [Google Scholar] [Crossref]

3. Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. [Google Scholar] [Crossref]

4. Boateng, F., & Agyeman, S. (2023). Artificial intelligence integration in performance management: Insights from Ghanaian enterprises. International Journal of Human Resource Studies, 13(1), 76–92. [Google Scholar] [Crossref]

5. Brynjolfsson, E., & McAfee, A. (2023). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. [Google Scholar] [Crossref]

6. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. [Google Scholar] [Crossref]

7. Guenole, N., Ferrar, J., & Feinzig, S. (2021). The power of people: How successful organizations use workforce analytics to improve business performance. Pearson Education. [Google Scholar] [Crossref]

8. Huang, M.-H., & Rust, R. T. (2021). Artificial intelligence in service. Journal of Service Research, 24(1), 3–24. [Google Scholar] [Crossref]

9. Kaplan, A., & Haenlein, M. (2023). Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Business Horizons, 66(2), 129–139. [Google Scholar] [Crossref]

10. Omondi, P., & Were, J. (2022). Challenges in the implementation of AI-driven systems in Kenyan workplaces. East African Journal of Business and Economics, 4(3), 55–71. [Google Scholar] [Crossref]

11. Trist, E. L., & Bamforth, K. W. (1951). Some social and psychological consequences of the longwall method of coal-getting. Human Relations, 4(1), 3–38. [Google Scholar] [Crossref]

12. World Economic Forum. (2023). Future of jobs report 2023: Navigating AI-driven transformations in the workforce. Geneva: World Economic Forum. [Google Scholar] [Crossref]

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