AI-driven organisational cognitive transformation: knowledge management strategies for hybrid cognition

Purpose This paper aims to position artificial intelligence (AI) as a knowledge-based cognitive technology that drives organisational cognitive transformation (OCT). This paper addresses three gaps in knowledge management (KM) theory. First, there is a need to further clarify the conceptualisation of AI’s cognitive role within a tradition that has attributed cognitive agency essentially to people, even as AI’s growing role requires such clarity. Second, treating AI as a generic technological capability is limiting; it requires distinguishing among different forms of human–AI cognitive integration and their differential effects on organisational hybrid cognition. Third, AI governance in relation to organisational decision-making and value creation is underdeveloped. Design/methodology/approach This paper adopts an integrative conceptual approach to theory building. The OCT construct is elucidated through a systematic literature review of 101 papers, spanning from Cyert and March (1963) to recent AI–cognition scholarship. This is complemented by a purposive, theory-driven review of the AI–KM literature, which identifies the mechanisms linking AI capabilities to organisational cognitive functions. Findings Organisational cognition is disaggregated into six interdependent dimensions that constitute an organisation’s cognitive architecture: interpretative framing, attentional allocation, distributed coordination of socio-material cognition, knowledge creation and learning, organisational memory and unlearning and epistemic authority and validation. A working definition of OCT is provided as the consequential reconfiguration of an organisational cognitive architecture, distinguished from digital transformation, organisational learning and socio-technical change. A functional, rather than ontological, conception of AI agency is discussed, acknowledging that AI produces artificial knowledge and accelerates the combination phase of knowledge conversion, while socialisation, internalisation and externalisation, together with epistemic authority over meaning and ethical accountability, remain human. Five AI-based KM strategies, for example, knowledge discovery and sensemaking, generative knowledge creation and co-production, reflexive learning, autonomous knowledge orchestration and co-evolutionary ecosystem intelligence, are proposed, and their impact on core KM processes and OCT dimensions is examined, recognising their complementary, contingent and cumulative nature within a path-dependent model of architectural reconfiguration. Research limitations/implications As a conceptual contribution, the framework requires empirical validation. Four propositions address adaptive sensemaking capacity, the moderating role of governance quality, the conditions under which generative knowledge artefacts strengthen dynamic capabilities and the risk of epistemic authority displacement. The six dimensions provide a basis for operationalising OCT and the impact of AI as a multi-dimensional construct in survey and case-based research. Practical implications AI adoption should be designed to drive cognitive architecture transformation rather than as a technology implementation. Managers should select their AI–KM strategies according to knowledge complexity, risk profile and governance readiness and embed epistemic, relational, technical and evolutionary governance from the outset, while addressing cognitive dependency, artificial certainty, interpretive overload and bias. Social implications This paper, highlighting AI adoption as an OCT, stresses that AI is transforming how organisations create and apply knowledge, with a significant impact on organisational value-creation mechanisms. Organisational cognition evolves, and human–AI integration assumes a central position. This has multiple implications for society, producing benefits such as improved complex decision-making and forecasting, but it also introduces risks when governance and accountability are inadequate. Originality/value This paper theorises OCT as a distinct construct, explains AI’s role as a driver of OCT, outlines forms of human–AI integration for organisational hybrid cognition and reconceptualises governance as constitutive of cognitive architecture rather than an ex post complement.