Challenges of Implementation of Artificial Intelligence in Managerial Human Resource - Khare, Gunjan (Digital Repository of Theses, 2024)
The incorporation of Artificial Intelligence (AI) into Managerial Human Resource (HR) management shows potential for improving decision-making processes, but it confronts considerable hurdles. This study investigates these challenges using survey responses to highlight critical areas for improvement, including defining and measuring staff performance, trust in AI-driven judgements, data privacy concerns, technical knowledge, and AI system costs. Key findings show that the subjective nature of performance evaluations, fragmented HR data, and transparency issues greatly impede AI implementation. To solve these issues, the report suggests standardising performance measurements, integrating HR systems, increasing AI transparency, and rigorously resolving data privacy concerns. The recommendations include developing clear, quantifiable performance criteria, unifying HR data into a unified platform, making AI processes public, and establishing strong data protection measures. These measures aim to establish a foundation of trust and efficiency, allowing for more seamless AI integration in HR tasks. Future study should look into the impact of standardised metrics on AI decision-making, the efficacy of integrated HR systems, the importance of transparency in fostering trust, and approaches to balance innovation and data privacy. By tackling these issues, organisations can better leverage AI's promise, assuring fair and successful HR decisions. This study emphasises the significance of strategic implementation and ethical issues in the use of AI in HR, proposing a path for overcoming current limits and optimising the benefits of AI technology in managerial HR.