Operational management and strategic scenarios of implementing artificial intelligence in entrepreneurship infrastructure organizations

The article examines the role of operational management in implementing various scenarios of artificial intelligence (AI) strategy adoption within entrepreneurship infrastructure organizations, such as chambers of commerce and industry, consulting firms, incubators, and government business support institutions. The study proposes a conceptual model that considers two key drivers: organizational readiness and the level of competitive pressure. The research methodology employs a matrix approach that identifies four AI implementation strategy scenarios. According to the Trailblazers scenario, AI is implemented by entrepreneurship infrastructure organizations with high readiness and high competitive pressure, which focus on aggressive innovation and rapid scaling. Organizations with low readiness but high pressure, concentrating on reactive solutions to achieve “quick wins” follow the Fast followers strategy. Cautious adopters have high readiness but low competitive pressure, allowing them to gradually integrate AI using proven solutions. Explorers are organizations with low readiness and low pressure that conduct experiments to accumulate knowledge. The research results demonstrate that the success of AI transformation largely depends on an organization's ability to adapt its operational strategy to its specific profile. Leading organizations (Trailblazers) require the creation of flexible teams and developed infrastructure, while catching-up organizations (Fast followers) can effectively use cloud AI services to quickly obtain results. For cautious adopters, risk management is a key aspect, and explorers focus on staff training and preparation for future changes. The practical value of the research lies in developing a strategy classification that helps organizations clearly identify their current state and choose the optimal AI implementation path. The proposed model serves as a tool for managers seeking to effectively integrate AI into their organizations' operations while considering their readiness levels and competitive environments. JEL Classification: O33, M15, L26

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Publication Details

Journal
Management and Entrepreneurship Trends of Development
Published
2025-01-01
DOI
https://doi.org/10.26661/2522-1566/2025-2/32-04
Citations
2
Primary Topic
Advanced Research in Systems and Signal Processing
Type
article
Field-Weighted Citation Impact
2.43
Controls
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article

Operational management and strategic scenarios of implementing artificial intelligence in entrepreneurship infrastructure organizations

Dmytro Antoniuk
2 citations
Management and Entrepreneurship Trends of Development
Advanced Research in Systems and Signal Processing
2.43
article

Operational management and strategic scenarios of implementing artificial intelligence in entrepreneurship infrastructure organizations

Dmytro Antoniuk
article en
2 citations

Abstract

The article examines the role of operational management in implementing various scenarios of artificial intelligence (AI) strategy adoption within entrepreneurship infrastructure organizations, such as chambers of commerce and industry, consulting firms, incubators, and government business support institutions. The study proposes a conceptual model that considers two key drivers: organizational readiness and the level of competitive pressure. The research methodology employs a matrix approach that identifies four AI implementation strategy scenarios. According to the Trailblazers scenario, AI is implemented by entrepreneurship infrastructure organizations with high readiness and high competitive pressure, which focus on aggressive innovation and rapid scaling. Organizations with low readiness but high pressure, concentrating on reactive solutions to achieve “quick wins” follow the Fast followers strategy. Cautious adopters have high readiness but low competitive pressure, allowing them to gradually integrate AI using proven solutions. Explorers are organizations with low readiness and low pressure that conduct experiments to accumulate knowledge. The research results demonstrate that the success of AI transformation largely depends on an organization's ability to adapt its operational strategy to its specific profile. Leading organizations (Trailblazers) require the creation of flexible teams and developed infrastructure, while catching-up organizations (Fast followers) can effectively use cloud AI services to quickly obtain results. For cautious adopters, risk management is a key aspect, and explorers focus on staff training and preparation for future changes. The practical value of the research lies in developing a strategy classification that helps organizations clearly identify their current state and choose the optimal AI implementation path. The proposed model serves as a tool for managers seeking to effectively integrate AI into their organizations' operations while considering their readiness levels and competitive environments. JEL Classification: O33, M15, L26

Management and Entrepreneurship Trends of DevelopmentVol. 2(32)
National University Zaporizhzhia Polytechnic (UA)
Decent work and economic growth
Openalex Percentile: Top 11%
Advanced Research in Systems and Signal Processing
2.43
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