The Impact of AI-Driven Performance Evaluation on Organizational Outcomes in Kenya: A Systematic Literature Review
DOI:
https://doi.org/10.53819/81018102t7040Abstract
This study explored the impact of AI-driven performance evaluation on organizational outcomes across various sectors in Kenya. Employing a desktop review methodology, it synthesized insights from academic literature, policy documents, and industry reports relevant to Kenya’s socioeconomic context. Thematic analysis highlighted core themes such as workforce productivity, decision-making, and risk management. Findings revealed that AI-driven performance evaluation significantly enhances organizational outcomes by improving decision-making accuracy, optimizing workforce management, and reinforcing risk management practices. However, adoption in Kenyan organizations faces barriers such as high costs, limited IT infrastructure, and data privacy concerns, particularly affecting small and medium-sized enterprises (SMEs). The study concludes that while AI-driven performance evaluation holds immense potential to improve organizational outcomes, its success depends on strategic, context-specific implementation and robust regulatory frameworks to address ethical and data privacy challenges. Policymakers are urged to establish comprehensive guidelines for ethical AI adoption, develop affordable AI solutions for SMEs, and invest in IT infrastructure and workforce training to maximize AI's benefits.
Keywords: AI-driven performance evaluation, organizational outcomes, productivity, decision-making, Kenya, organizational readiness theory, resource-based view, public administration, SMEs, risk management, AI adoption, workforce productivity, sustainable growth
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