Artificial intelligence and human-in-loop: a complementary approach to workplace coaching

Purpose This study aims to investigate the role of artificial intelligence (AI) in workplace coaching and to provide a framework for integrating AI and human intelligence to enhance employee learning and development. Design/methodology/approach This study employs a comprehensive review of existing literature, focusing on understanding the role of humans in the loop while integrating AI systems into workplace learning processes. Data for the review were collected from the Google Scholar database using the search criteria (“Artificial Intelligence Coach” OR “AI coach”) AND (“Human Coach” OR “Workplace Learning” OR Organizational Development” OR “Human-AI integration”). We further filtered the results to the Management and Business categories, followed by the abstract review to identify the final articles considered for the review. Findings The review highlights the growing utility of AI in providing insights, feedback, and decision support while underscoring its limitations in promoting empathetic response, critical thinking, ethical judgment, and adaptive learning. The proposed AI-HIL framework emphasizes the complementary roles of humans and AI in workplace coaching, ensuring humans remain actively engaged in monitoring, decision-making, and contextual interpretation. Comparative insights suggest that combining human expertise with AI’s analytical capabilities can optimize learning outcomes, trust, and engagement within organizations. Research limitations/implications Future research should investigate how long-term repeated interactions with AI-HIL systems affect employee learning outcomes, trust, engagement, and reliance on AI over time. Scholars might also explore the extent of human monitoring and the level of autonomy required to achieve optimal learning outcomes. Comparative studies of AI and human coaching, both independently and collaboratively, could provide further clarity on the differential impacts on the emotional, cognitive, and behavioral development of employees within organizational learning contexts. Practical implications The AI-HIL Complementary Coaching Framework emphasizes that organizations should not rely solely on AI systems; instead, AI should serve as an augmentative tool that supports and enhances human coaching, decision-making, and learning. In addition, managers and leaders play a crucial role as experts, guiding the AI-generated insights using human intelligence and empathetic support. Furthermore, the socio-technical alignment necessitates that organizations integrate AI tools into workflows that facilitate meaningful human participation. This includes providing human coaches with access to AI-generated insights, training them to effectively interpret and act on these insights, and establishing mechanisms to monitor and correct AI outputs to prevent errors or bias. Originality/value This study contributes a novel conceptual framework that integrates AI and HIL principles, addressing a gap in understanding how AI can augment rather than replace human coaching in the workplace.