Effect of Generative Artificial Intelligence on Strategic Decision-Making in Entrepreneurial Business Initiatives: A Systematic Literature Review

Generative Artificial Intelligence (GAI) is emerging as a promising tool with which to improve strategic decision-making in a business environment characterized by increasing complexity. There are external and internal factors that are part of the success of entrepreneurial initiatives. Relevant factors that make decision-making effective include the technological environment, as an external factor, and innovation, as an internal factor. Methods: This study reviews the existing literature on implementing GAI in business decision-making. It assesses its short-, medium- and long-term effects, considering the interaction between GAI and human judgment. Challenges related to uncertainty, complexity, and ambiguity are examined, and the relevant literature is reviewed to understand these aspects comprehensively. Results: The review shows that, despite the advanced capabilities of GAI to analyze data and generate patterns, human judgment remains crucial in situations of high uncertainty. The results suggest that combining GAI with human expertise can improve the accuracy and efficiency of strategic decision-making by integrating the strengths of both parties. Conclusions: The implementation of GAI can offer significant improvements in the efficiency and accuracy of business decisions. However, human judgment and experience remain essential, especially in uncertain contexts. The key to maximizing the benefits of GAI lies in finding the right balance between artificial intelligence and human capital.

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Publication Details

Journal
Administrative Sciences
Published
2025-02-18
DOI
https://doi.org/10.3390/admsci15020066
Citations
26
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
59.38
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article

Effect of Generative Artificial Intelligence on Strategic Decision-Making in Entrepreneurial Business Initiatives: A Systematic Literature Review

Diego Mauricio Bonilla Jurado, Patricia Acosta-Vargas, Óscar López, Mayra Bedoya Jara et al.
26 citations
Administrative Sciences
Big Data and Business Intelligence
59.38
article

Effect of Generative Artificial Intelligence on Strategic Decision-Making in Entrepreneurial Business Initiatives: A Systematic Literature Review

Diego Mauricio Bonilla Jurado, Patricia Acosta-Vargas, Óscar López, Mayra Bedoya Jara, Joselito Naranjo-Santamaría, Héctor Alberto Luzuríaga Jaramillo
article en
26 citations

Abstract

Generative Artificial Intelligence (GAI) is emerging as a promising tool with which to improve strategic decision-making in a business environment characterized by increasing complexity. There are external and internal factors that are part of the success of entrepreneurial initiatives. Relevant factors that make decision-making effective include the technological environment, as an external factor, and innovation, as an internal factor. Methods: This study reviews the existing literature on implementing GAI in business decision-making. It assesses its short-, medium- and long-term effects, considering the interaction between GAI and human judgment. Challenges related to uncertainty, complexity, and ambiguity are examined, and the relevant literature is reviewed to understand these aspects comprehensively. Results: The review shows that, despite the advanced capabilities of GAI to analyze data and generate patterns, human judgment remains crucial in situations of high uncertainty. The results suggest that combining GAI with human expertise can improve the accuracy and efficiency of strategic decision-making by integrating the strengths of both parties. Conclusions: The implementation of GAI can offer significant improvements in the efficiency and accuracy of business decisions. However, human judgment and experience remain essential, especially in uncertain contexts. The key to maximizing the benefits of GAI lies in finding the right balance between artificial intelligence and human capital.

Administrative SciencesVol. 15(2)
Universidad de Las Américas (EC), Universidad Técnica de Ambato (EC)
Openalex Percentile: Top 0%
Big Data and Business Intelligence
59.38
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