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Understanding AI innovation contexts: a review and content analysis of artificial intelligence and entrepreneurial ecosystems research

Philip T. Roundy (The University of Tennessee at Chattanooga, Chattanooga, Tennessee, USA)
Arben Asllani (The University of Tennessee at Chattanooga, Chattanooga, Tennessee, USA)

Industrial Management & Data Systems

ISSN: 0263-5577

Article publication date: 4 June 2024

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Abstract

Purpose

An emerging research stream focuses on the place-based ecosystems where artificial intelligence (AI) innovations emerge and develop. This literature builds on the contextual turn in management research and, specifically, work on entrepreneurial ecosystems. However, as a nascent research area, the literature on AI and entrepreneurial ecosystems is fragmented across academic and practitioner boundaries and unconnected disciplines because of disparate and ill-defined concepts. As a result, the literature is disorganized and its main insights are latent. The purpose of this paper is to synthesize research on AI ecosystems and identify the main insights.

Design/methodology/approach

We first consolidate research on the “where” of AI innovation through a scoping review. To address the fragmentation in the literature and understand how entrepreneurial ecosystems are associated with AI innovation, we then use content analysis to explore the literature.

Findings

We identify the main characteristics of the AI and ecosystems literature and the key dimensions of “AI entrepreneurial ecosystems”: the local actors and factors in geographic territories that are coordinated to support the creation and development of AI technologies. We clarify the relationships among AI technologies and ecosystem dimensions and uncover the latent themes and underlying structure of research on AI entrepreneurial ecosystems.

Originality/value

We increase conceptual precision by introducing and defining an umbrella concept—AI entrepreneurial ecosystem—and propose a research agenda to spur further insights. Our analysis contributes to research at the intersection of management, information systems, and entrepreneurship and creates actionable insights for practitioners influenced by the geographic agglomeration of AI innovation.

Keywords

Citation

Roundy, P.T. and Asllani, A. (2024), "Understanding AI innovation contexts: a review and content analysis of artificial intelligence and entrepreneurial ecosystems research", Industrial Management & Data Systems, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IMDS-08-2023-0551

Publisher

:

Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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