<![CDATA[Despite the growing deployment of agentic AI in enterprise settings, no theoretical framework exists for integrating it as an active co-facilitator of organisational learning within executive consulting practice. This paper develops the Agentic Organizational Learning Facilitation (AOLF) Framework, which positions agentic AI as a structured co-facilitator across the full cycle of executive consulting engagements. An integrative conceptual analysis methodology was employed, synthesising interdisciplinary literature from organisational learning theory, adult learning and instructional design, and agentic AI scholarship through a four-stage process of scoping, thematic synthesis, framework construction, and internal validation. The resulting framework comprises four iterative phases, Diagnose, Design and Facilitate, Reflect and Surface, and Adapt and Reframe grounded in double-loop learning theory, andragogy, the ADDIE instructional model, and the Community of Inquiry framework. The framework proposes that agentic AI can support double-loop learning and adaptive knowledge creation at a scale individual human consultants cannot sustain alone, while human consultants retain responsibility for relational and ethically sensitive dimensions. Three theoretical contributions are advanced: extending double-loop learning theory to AI-mediated facilitation; introducing the construct of agentic presence as an expansion of the Community of Inquiry model; and a co-facilitation model that challenges the assumption of an exclusively human facilitator role in andragogy. Practical implications address AI-augmented consulting design, data governance, supervised autonomy, and prevention of consultant deskilling.]]>
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