Human-in-the-Loop AI in HR Decision-Making: Insights from Big 4 AI Governance Reports

Year : 2026 | Volume : 16 | Issue : 01 | Page : 43 50
    By

    Laxmee Vachher,

  • Shyamali Dubey,

  1. Associate Professor, School of Management, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India
  2. Associate Professor, School of Management, Babu Banarasi Das University, Lucknow, Uttar Pradesh, India

Abstract

The integration of artificial intelligence (AI) in human resource (HR) decision-making has transformed recruitment, performance evaluations, and talent management. However, biases embedded in AI-driven HR systems present significant ethical and operational challenges. Human-in-the-Loop (HITL) AI offers a hybrid approach that combines AI efficiency with human oversight to enhance fairness and accountability. This paper systematically analyses HITL AI in HR decision-making using qualitative analysis of AI governance reports from Big 4 consulting firms. Findings indicate that HITL AI enhances fairness and compliance in HR decisions but faces challenges in scalability, workforce acceptance, and regulatory complexity. The study provides insights into governance frameworks and best practices for balancing AI efficiency with human oversight. Additionally, this paper builds upon prior research on AI bias in HR analytics by extending the discussion towards practical implementations of HITL frameworks and assessing their effectiveness through industry insights.

Keywords: AI governance, human-in-the-loop AI, HR analytics, Big 4 consulting, algorithmic bias, ethical AI, explainable AI (XAI)

[This article belongs to Current Trends in Information Technology ]

How to cite this article:
Laxmee Vachher, Shyamali Dubey. Human-in-the-Loop AI in HR Decision-Making: Insights from Big 4 AI Governance Reports. Current Trends in Information Technology. 2026; 16(01):43-50.
How to cite this URL:
Laxmee Vachher, Shyamali Dubey. Human-in-the-Loop AI in HR Decision-Making: Insights from Big 4 AI Governance Reports. Current Trends in Information Technology. 2026; 16(01):43-50. Available from: https://journals.stmjournals.com/ctit/article=2026/view=236628


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Regular Issue Subscription Review Article
Volume 16
Issue 01
Received 15/09/2025
Accepted 20/09/2025
Published 07/02/2026
Publication Time 145 Days
357

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