Strategic Edge Architecture: AI-Augmented Cognitive Infrastructure for SME Adaptability and Sustainable Growth

Small- and medium-sized enterprises (SMEs) operate under conditions of rapid change, competitive pressure and growing informational complexity, while their owner-managers often have limited time and cognitive bandwidth to interpret emerging strategic possibilities. Artificial intelligence (AI) is beginning to change this by extending how firms detect signals, interpret shifting environments and evaluate possible strategic responses. However, existing work in dynamic capabilities, sensemaking and microfoundations does not fully explain how AI-augmented cognitive systems shape organisational interpretive capacity, strategic adaptability and sustainable competitive positioning. This article addresses that gap by developing Strategic Edge Architecture (SEA), a sociotechnical microfoundational theory of how AI-augmented cognitive infrastructure enhances environmental sensing, prospective sensemaking, adaptive strategic response and sustainability integration in SMEs. Drawing on a multiparadigm theoretical synthesis, this article integrates insights from strategic management, organisational cognition, microfoundations, AI governance and sustainability strategy. SEA conceptualises strategic capability as an emergent property of cognitive infrastructure within which human and AI systems interact to support environmental interpretation, strategic adaptation and sustainable growth. The framework proposes a causal pathway through which AI augmentation strengthens sensing and sensemaking, with human-in-the-loop governance acting as a key moderating condition. The article concludes with formal propositions to guide future empirical research on AI-augmented organisational cognition, whilst recognising that the framework’s claims remain inferential and require empirical examination before SEA’s explanatory power can be assessed.

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Publication Details

Journal
Administrative Sciences
Published
2026-06-16
DOI
https://doi.org/10.3390/admsci16060291
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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article

Strategic Edge Architecture: AI-Augmented Cognitive Infrastructure for SME Adaptability and Sustainable Growth

Grant Freedman
Administrative Sciences
Big Data and Business Intelligence
article

Strategic Edge Architecture: AI-Augmented Cognitive Infrastructure for SME Adaptability and Sustainable Growth

Grant Freedman
article en

Abstract

Small- and medium-sized enterprises (SMEs) operate under conditions of rapid change, competitive pressure and growing informational complexity, while their owner-managers often have limited time and cognitive bandwidth to interpret emerging strategic possibilities. Artificial intelligence (AI) is beginning to change this by extending how firms detect signals, interpret shifting environments and evaluate possible strategic responses. However, existing work in dynamic capabilities, sensemaking and microfoundations does not fully explain how AI-augmented cognitive systems shape organisational interpretive capacity, strategic adaptability and sustainable competitive positioning. This article addresses that gap by developing Strategic Edge Architecture (SEA), a sociotechnical microfoundational theory of how AI-augmented cognitive infrastructure enhances environmental sensing, prospective sensemaking, adaptive strategic response and sustainability integration in SMEs. Drawing on a multiparadigm theoretical synthesis, this article integrates insights from strategic management, organisational cognition, microfoundations, AI governance and sustainability strategy. SEA conceptualises strategic capability as an emergent property of cognitive infrastructure within which human and AI systems interact to support environmental interpretation, strategic adaptation and sustainable growth. The framework proposes a causal pathway through which AI augmentation strengthens sensing and sensemaking, with human-in-the-loop governance acting as a key moderating condition. The article concludes with formal propositions to guide future empirical research on AI-augmented organisational cognition, whilst recognising that the framework’s claims remain inferential and require empirical examination before SEA’s explanatory power can be assessed.

Administrative SciencesVol. 16(6)
Nelson Mandela University (ZA)
DeepMind
Industry, innovation and infrastructure
Openalex Percentile: Top 4%
Big Data and Business Intelligence
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