Purpose While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain. Design/methodology/approach A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the "AI-enabled entrepreneurial process." Findings This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research. Practical implications The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting. Originality/value This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature.

Giuggioli, G., Pellegrini, M. (2022). Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research. INTERNATIONAL JOURNAL OF ENTREPRENEURIAL BEHAVIOUR & RESEARCH [10.1108/IJEBR-05-2021-0426].

Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research

Pellegrini, M
2022-01-01

Abstract

Purpose While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain. Design/methodology/approach A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the "AI-enabled entrepreneurial process." Findings This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research. Practical implications The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting. Originality/value This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature.
2022
Pubblicato
Rilevanza internazionale
Articolo
Esperti anonimi
Settore SECS-P/10 - ORGANIZZAZIONE AZIENDALE
English
Con Impact Factor ISI
Entrepreneurship
Artificial intelligence
Machine learning
Deep learning
Innovation
Technology
https://doi.org/10.1108/IJEBR-05-2021-0426
Giuggioli, G., Pellegrini, M. (2022). Artificial intelligence as an enabler for entrepreneurs: a systematic literature review and an agenda for future research. INTERNATIONAL JOURNAL OF ENTREPRENEURIAL BEHAVIOUR & RESEARCH [10.1108/IJEBR-05-2021-0426].
Giuggioli, G; Pellegrini, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/306343
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