This paper repositions reverse mentoring as a strategic enabler of adaptive leadership in AI-enabled organizations. It explores how reciprocal learning between digitally fluent junior professionals and senior leaders can foster digital capability, inclusivity, and organizational agility.
Grounded in Social Learning Theory and the Knowledge-Based View of the Firm, this conceptual study introduces a model linking reverse mentoring to behavioral and knowledge-based outcomes. The model is informed by literature and real-world practices.
Reverse mentoring facilitates senior leader adaptability, inclusive decision-making, and intergenerational trust. Junior mentors gain visibility and early leadership exposure, while senior leaders develop digital fluency and openness. The process is most effective when supported by psychological safety, role clarity, and structured feedback.
As a conceptual paper, the model proposed has not yet been empirically tested. Future studies should validate the framework using longitudinal and cross-industry data, and explore cultural and ethical dimensions, particularly in power-reversed learning contexts. Caution is also advised when generalizing across different organizational cultures.
Successful implementation requires intentional mentor–mentee pairing, cultural readiness, and continuous facilitation. Case insights from companies like GE, Accenture, and Unilever illustrate how reverse mentoring can support digital transformation and inclusion.
This paper contributes a theoretically grounded, practically relevant model of reverse mentoring for AI-era leadership development and identifies key design and implementation considerations.
