International Journal of Research and Scientific Innovation (IJRSI)
AI-Powered Performance Management: A Case Study in Accra
Published November 22, 2025 • Vol. 12, Issue 10, pp. 3919–3923Open Access
DOI: 10.51244/IJRSI.2025.1210000337
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
| Journal | International Journal of Research and Scientific Innovation (IJRSI) |
|---|---|
| ISSN | 2321-2705 |
| Volume / Issue | Volume 12, Issue 10 |
| Pages | 3919–3923 |
| Publication date | November 22, 2025 |
| DOI | 10.51244/IJRSI.2025.1210000337 |
| Publisher | RSIS International |
| License | Open Access |
How to cite this article
Samuel Asante (2025). AI-Powered Performance Management: A Case Study in Accra. International Journal of Research and Scientific Innovation (IJRSI), 12(10), 3919-3923. https://doi.org/10.51244/IJRSI.2025.1210000337
BibTeX
@article{Samuel2025,
title = {AI-Powered Performance Management: A Case Study in Accra},
author = {Samuel Asante},
journal = {International Journal of Research and Scientific Innovation (IJRSI)},
volume = {12},
number = {10},
pages = {3919--3923},
year = {2025},
doi = {10.51244/IJRSI.2025.1210000337},
publisher = {RSIS International}
}