Artificial Intelligence and firm strategies: A pathway to enhanced productivity
Syed Muhammad Ali Shah, Marco Cucculelli · Journal of Strategy & Innovation · 2 Jul 2026
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Where this sits in the debate
- Will AI actually boost productivity and growth? · its finding: it depends (why studies differ)
Direction of the finding as read from the abstract by an AI model (AI-written).
Key takeaway AI-written
Combining LinkedIn skills data with website-derived strategy information for 1,800 manufacturing firms, the study estimates a production function and finds higher AI intensity is associated with higher production efficiency. The association is strongest for internationally oriented firms and absent for firms whose strategic goal is environmental sustainability.
Abstract
This study examines the strategic impact of artificial intelligence (AI) on firm productivity, with a focus on how different strategic goals – customer centricity, international market expansion, and environmental sustainability - interact with AI adoption. We combine professional skills data from LinkedIn with information on innovation activities and strategic objectives collected from company websites for a sample of 1800 manufacturing firms. Using an augmented Cobb–Douglas production function and a two-stage estimation approach, our analysis shows that firms with higher levels of AI intensity tend to exhibit higher production efficiency. However, firms emphasizing customer centricity tend to be less productive, while firms combining higher AI intensity with an international market orientation tend to exhibit higher productivity. By contrast, we find no statistically significant link between AI use and productivity when the strategic goal is environmental sustainability. Overall, the study fills a gap in understanding the role of AI in shaping firm productivity across different strategic orientations, offering valuable insights for optimizing AI intensity and aligning it with strategic planning.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
- Published
- 2026 (4 months ago)
- Citations
- 0 (OpenAlex)
0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison.
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