Operational management and strategic scenarios of implementing artificial intelligence in entrepreneurship infrastructure organizations
DOI:
https://doi.org/10.26661/2522-1566/2025-2/32-04Keywords:
entrepreneurship infrastructure organisations, operational management, artificial intelligence, digital transformation, business processes, organizational readiness, competitive pressureAbstract
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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