Oct 2026· Foresight· pp. 1-15· 0 citations· 34 references
TL;DR
This study reconceptualises AI as constitutive of organisational foresight instead of an instrument applied to it, introduces and differentiates anticipatory co-evolution as a novel construct, and integrates Rohrbeck’s maturity model with Ivanov’s configuration taxonomy.
Abstract
Research on artificial intelligence (AI) in organisations has concentrated on operational efficiency and automation. This study aims to reposition AI as both a constitutive element and a strategic object of foresight, a dual role the literature has noticed but not theorised.
A narrative literature review draws peer-reviewed work from foresight studies, socio-technical systems theory and organisational change into an integrated analytical framework. Selection prioritised conceptual contribution, transparency of reasoning and relevance to AI in strategic futures thinking.
AI strengthens environmental sensing, complex modelling and scenario work under uncertainty. The framework has four components: inputs, AI systems, human–AI interaction and outcomes, and yields five propositions for empirical testing.
As a theoretical contribution, empirical validation remains a priority. Findings should be tested across sectors and organisational contexts before generalisation.
Organisations must cultivate digital foresight literacy, restructure around cross-functional foresight teams and implement agile governance capable of auditing AI-generated outputs. The framework provides guidance for navigating algorithmic bias, transparency obligations and power asymmetries.
This study makes four contributions. It reconceptualises AI as constitutive of organisational foresight instead of an instrument applied to it, introduces and differentiates anticipatory co-evolution as a novel construct, integrates Rohrbeck’s (2010) maturity model with Ivanov’s (2023) configuration taxonomy and sets out ethical governance requirements specific to AI-enabled foresight.
The paper contributes to Knowledge Management by reframing strategic intelligence as a governance problem and by linking qualitative evidence from doctoral research to the current proof-of-concept implementation of the framework.
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