AI-Powered Employee Performance Evaluation Systems in HR Management

Employee performance evaluation is essential in human
resource management, but existing systems are typically
subjective and inefficient, resulting in skewed results and
employee dissatisfaction. The paper addresses these limitations by
introducing an AI-powered employee performance rating system.
The system uses data-driven insights and powerful algorithms to
provide objective assessments, improving objectivity, fairness,
and efficiency in the review process. The proposed
system provides real-time feedback and insights by combining
extensive data collection and integration, Machine learning (ML)
model selection, NLP analysis, and explainable AI methodologies,
allowing HR managers to make educated decisions and
successfully support employee development. The results and
analysis show that the AI-powered system outperforms
conventional approaches, with accuracy values ranging from 0.78
to 0.85, precision values from 0.79 to 0.86, and recall values
ranging from 0.76 to 0.84. These results demonstrate AI
technology's potential to promote organizational success by
improving performance evaluation systems, encouraging staff
development, and gaining a competitive advantage in the
marketplace.