MJSTEM

Abstract

Artificial Intelligence (AI) is quickly changing Human Resource (HR) practices in organizations worldwide, with India's Information Technology (IT) sector leading this change. This paper presents a systematic literature review employing the Theory–Context–Characteristics–Methodology (TCCM) framework to evaluate the effectiveness of AI in HR functions, namely recruitment and selection, performance management, employee engagement, learning and development, and workforce analytics. Drawing on 52 peer-reviewed studies published between 2018 and 2025, along with authoritative industry reports from NASSCOM, McKinsey, Gartner, SHRM, and the World Economic Forum, this review synthesizes the theoretical framework, contextual deployment patterns, key constructs of effectiveness, and dominant research methodologies. The global AI-in-HR market, valued at USD 3.25 billion in 2023 and projected to reach USD 15.24 billion by 2030 (CAGR 24.8%), underscores the urgency of a rigorous evaluation. In India, 72% of organizations have integrated AI into HR software (Capterra, 2025), with the IT sector showing the highest adoption intensity. The review identifies significant research gaps, particularly the absence of region-specific empirical studies from emerging IT corridors such as Madhya Pradesh, and proposes a conceptual model for contextualized AI–HR effectiveness. The findings offer theoretical contributions and practical implications for HR practitioners, policymakers, and future researchers.

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