Applications of Artificial Intelligence ( <scp>AI</scp> ) in Business Entrepreneurship and Start‐Ups: A Systematic Literature Review and Bibliometric Analysis

ABSTRACT Artificial Intelligence (AI) is transforming entrepreneurship by enabling data‐driven innovation, strategic decision‐making, and operational agility; however, its adoption remains uneven and fragmented due to technological, organizational, and contextual barriers. This study examines the applications, trends, and intellectual structure of AI‐driven entrepreneurship through a systematic literature review and bibliometric analysis, employing the SPAR‐4‐SLR protocol to analyze peer‐reviewed English‐language articles retrieved from the Scopus database published between 2004 and 2025. The performance analysis and science mapping of 245 relevant publications was done using Biblioshiny and VOSviewer. The results demonstrate that the research output has increased exponentially since 2018 as a result of the merging of AI technologies and entrepreneurial innovation. Major AI applications have been found in marketing and customer interaction, product development and innovation, decision‐making and strategy, financing, entrepreneurship education, and operational performance. The factors that support adoption include technological readiness, data‐driven culture, and capability development, whereas the hindering ones are the lack of resources, the problem with data quality, and ethical and governance concerns. Thematic and key‐word co‐occurrence analyses demonstrate the emergent research areas of AI‐enabled entrepreneurship, digital transformation, innovation, and generative AI, which highlights the increased interdisciplinarity of the domain. This study presents organized thematic taxonomy and suggests a future research paradigm, which can be of great use to researchers, entrepreneurs and policymakers who would be running AI‐based entrepreneurial ecosystems.

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Publication Details

Journal
Applied AI Letters
Published
2026-05-11
DOI
https://doi.org/10.1002/ail2.70031
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

Applications of Artificial Intelligence ( AI ) in Business Entrepreneurship and Start‐Ups: A Systematic Literature Review and Bibliometric Analysis

Abdul Bashiru Jibril, Jacob Muvingi, Mohit Yadav, Mohan Kumar et al.
Applied AI Letters
AI in Service Interactions
article

Applications of Artificial Intelligence ( AI ) in Business Entrepreneurship and Start‐Ups: A Systematic Literature Review and Bibliometric Analysis

Abdul Bashiru Jibril, Jacob Muvingi, Mohit Yadav, Mohan Kumar, John Amoah, Perfecto G. Aquino
article en

Abstract

ABSTRACT Artificial Intelligence (AI) is transforming entrepreneurship by enabling data‐driven innovation, strategic decision‐making, and operational agility; however, its adoption remains uneven and fragmented due to technological, organizational, and contextual barriers. This study examines the applications, trends, and intellectual structure of AI‐driven entrepreneurship through a systematic literature review and bibliometric analysis, employing the SPAR‐4‐SLR protocol to analyze peer‐reviewed English‐language articles retrieved from the Scopus database published between 2004 and 2025. The performance analysis and science mapping of 245 relevant publications was done using Biblioshiny and VOSviewer. The results demonstrate that the research output has increased exponentially since 2018 as a result of the merging of AI technologies and entrepreneurial innovation. Major AI applications have been found in marketing and customer interaction, product development and innovation, decision‐making and strategy, financing, entrepreneurship education, and operational performance. The factors that support adoption include technological readiness, data‐driven culture, and capability development, whereas the hindering ones are the lack of resources, the problem with data quality, and ethical and governance concerns. Thematic and key‐word co‐occurrence analyses demonstrate the emergent research areas of AI‐enabled entrepreneurship, digital transformation, innovation, and generative AI, which highlights the increased interdisciplinarity of the domain. This study presents organized thematic taxonomy and suggests a future research paradigm, which can be of great use to researchers, entrepreneurs and policymakers who would be running AI‐based entrepreneurial ecosystems.

Applied AI LettersVol. 7(2)
Duy Tan University (VN), Vietnam National University, Hanoi (VN), University of Kurdistan Hewler (IQ), Department of Commerce (AU), O. P. Jindal Global University (IN), Takoradi Technical University (GH)
Decent work and economic growth
Openalex Percentile: Top 6%
AI in Service Interactions
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