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Purpose

This study aims to examine how employees informally create and share knowledge about artificial intelligence (AI) tools outside formal organisational systems. The authors term this phenomenon “shadow knowledge creation”, the informal, unsanctioned experimentation through which organisational AI capabilities emerge outside formal training and development programmes.

Design/methodology/approach

Through conceptual analysis grounded in knowledge management and organisational learning theory, this paper advances the beyond-training framework. The analysis integrates sociomaterial perspectives on knowledge creation with illustrative cases demonstrating how tacit AI knowledge flows through informal networks.

Findings

Shadow knowledge creation poses a distinct challenge to formal training and knowledge management systems, calling for an organisational response that engages with informal AI experimentation instead of displacing it. The beyond-training framework offers four principles for that response: recognition, integration, ethics and empowerment. The beyond-training framework provides mechanisms for capturing this distributed knowledge without destroying the informal dynamics that generate it.

Research limitations/implications

The conceptual model requires empirical validation across diverse organisational contexts. Future research should examine how shadow knowledge creation varies by industry, organisational culture and AI maturity.

Practical implications

Training and development professionals and managers receive actionable guidance for applying the four principles in practice: recognising informal AI knowledge creation, integrating it with formal systems, supporting ethical experimentation and empowering employees with the time, tools and trust the work requires.

Originality/value

This paper introduces “shadow knowledge creation” as a novel theoretical lens for understanding informal AI knowledge development. It contributes a schema that bridges individual tacit knowledge acquisition with organisational knowledge management systems, addressing a critical gap in training and development scholarship regarding how AI capabilities emerge in organisations.

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