Journal article
Coaching leaders for transformative learning: a hybrid intelligence framework for integrating human and AI coaches
Journal of work-applied management, pp 1-14
14 May 2026
Abstract
Purpose-Organizations are increasingly relying on the power of coaching not only to support and develop leaders but also to create sustainable, deep transformational change. As in many domains, artificial intelligence (AI) has entered the coaching arena. Human resource (HR) practitioners responsible for offering coaching to leaders now face a new challenge: how to integrate the cognitive power of AI with the relational depth of human coaches to support leaders with deep, transformative learning (TL). Design/methodology/approach-This non-empirical, conceptual paper addresses that challenge by proposing a hybrid intelligence model where AI and human coaches work collaboratively to guide leaders through the ten stages of Mezirow's TL process. Findings-Using a fictional narrative vignette of Jaya, a senior leader facing a leadership identity crisis, the paper illustrates how AI excels at structured diagnostics, pattern recognition and goal-tracking, yet struggles with emotional resonance and contextual sensitivity. In contrast, human coaches bring empathy, trust and the capacity to hold meaning-making conversations, essential for TL. Originality/value-We propose the first hybrid intelligence integrated framework to guide when and how AI or human coaches should take the lead across each stage of transformation. We offer organizations, HR, coaches and AI developers a roadmap for deploying hybrid coaching models that balance efficiency with empathy and insight with connection to help leadership coaching remain effective, accessible and deeply human in an increasingly automated world.
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Details
- Title
- Coaching leaders for transformative learning: a hybrid intelligence framework for integrating human and AI coaches
- Creators
- Nicky Terblanche - Stellenbosch UniversityRajashi Ghosh - University of Missouri
- Publication Details
- Journal of work-applied management, pp 1-14
- Publisher
- Emerald Group Publishing
- Number of pages
- 14
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Education
- Web of Science ID
- WOS:001764608800001
- Other Identifier
- 991022182775704721