Adoption of Artificial Intelligence in Performance Management Systems: Key Influencing Factors and Adoption Rates

The adoption of Artificial Intelligence (AI) in performance management systems is transforming how
organizations evaluate, monitor, and enhance employee performance. This study explores the key factors influencing
AI adoption in performance management and examines current adoption rates across industries. Using a descriptive
research approach, the study relies on secondary data sources, including industry reports, academic literature, and
market surveys. Findings highlight critical drivers such as technological readiness, organizational culture, cost
considerations, and regulatory concerns. Additionally, the research identifies barriers to adoption, including ethical
challenges such as data privacy issues, bias, transparency and integration challenge. By analysing adoption trends, this
study provides valuable insights into the growing role of AI in optimizing performance management practices.
Organizations must balance automation with human judgment to ensure equitable evaluations and foster employee
trust. The findings contribute to a deeper understanding of how AI adoption is shaping modern workforce management
and offer guidance for organizations considering AI-driven performance solutions.