Open Innovation and Artificial Intelligence: New Dimensions of Innovation Management
DOI:
https://doi.org/10.15170/MM.2025.59.KSZ.01.05Keywords:
Artificial intelligence (AI), Open Innovation, Innovation management, collaborationAbstract
THE AIM OF THE PAPER
The study aims to explore how artificial intelligence (AI) technologies support open innovation processes and to identify the most important trends and research directions. It highlights the significance of the relationship between AI and open innovation in transforming innovation management and establishing sustainable economic models. Furthermore, the study emphasizes how AI can create new opportunities for collaboration between companies and scientific communities.
METHODOLOGY
The research is based on a systematic literature review and keyword co-occurrence analysis conducted using relevant publications from the Scopus database. The VOSviewer software was used to identify the main thematic clusters of the relationship between AI and open innovation, including digitalization, enhancing innovation capabilities, strengthening collaborative culture, and boosting strategic competitiveness. The analysis considered the period from 2000 to 2023, providing a comprehensive overview of the latest trends.
MOST IMPORTANT RESULTS
The analysis identified four key areas: AI-driven digitalization, enhancing innovation capabilities, strengthening collaborative culture, and boosting strategic competitiveness. The findings revealed that AI not only accelerates the pace of innovation but also creates new opportunities in collaboration and decision-making processes. For instance, the application of predictive analytics significantly improves strategic decision-making, while AI-based automation promotes more efficient resource utilization. The study highlighted that AI-based approaches offer significant advantages in achieving faster market entry and sustainable innovation.
RECOMMENDATIONS
The study recommends the integration of AI into innovation management practices, particularly in data-driven decision-making and digital transformation. From a policy perspective, it is crucial to establish regulatory frameworks that ensure the transparent and ethical application of AI. These frameworks can facilitate sustainable innovation processes while supporting open collaboration between companies. Special attention should be given to the development of AI training programs to promote broader acceptance and application of the technology across various industries.
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