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From potential to practice: barriers and risk to artificial intelligence adoption in renewable energy operations & maintenance and devolution of the industry onshore wind in German: a market entry strategy
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This work project investigates the barriers and future opportunities for Artificial Intelligence adoption in operations and maintenance within the wind energy sector. Using the TOE framework and insights from semi-structured expert interviews, the study identifies technological, organizational, and environmental constraints that limit adoption. Horizon scanning reveals how artificial intelligence could evolve from a supportive tool to a key orchestrator in decentralized energy systems. The project offers strategic recommendations for the Company and similar firms to leverage artificial intelligence in targeted use cases, driving efficiency and resilience in an increasingly competitive and digitized renewable energy landscape.
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Renewable energy Artificial intelligence Operations & Maintenance Innovation CEMS MIM