Artificial Intelligence and Sustainable Practices in Coastal Marinas: A Comparative Study of Monaco and Ibiza

Artificial intelligence (AI) is playing an increasingly important role in driving sustainable change across coastal and marine environments. Artificial intelligence offers strong support for environmental decision-making by helping to process complex data, anticipate outcomes, and fine-tune day-to-day operations. In busy coastal zones such as the Mediterranean where tourism and boating place significant strain on marine ecosystems, AI can be an effective means for marinas to reduce their ecological impact without sacrificing economic viability. This research examines the contribution of artificial intelligence toward the development of environmental sustainability in marina management. It investigates how AI can potentially reconcile economic imperatives with ecological conservation, especially in high-traffic coastal areas. Through a focus on the impact of social and technological context, this study emphasizes the way in which local conditions constrain the design, deployment, and reach of AI systems. The marinas of Ibiza and Monaco are used as a comparative backdrop to depict these dynamics. In Monaco, efforts like the SEA Index® and predictive maintenance for superyachts contributed to a 28% drop in CO2 emissions between 2020 and 2025. In contrast, Ibiza focused on circular economy practices, reaching an 85% landfill diversion rate using solar power, AI-assisted waste systems, and targeted biodiversity conservation initiatives. This research organizes AI tools into three main categories: supervised learning, anomaly detection, and rule-based systems. Their effectiveness is assessed using statistical techniques, including t-test results contextualized with Cohen’s d to convey practical effect sizes. Regression R2 values are interpreted in light of real-world policy relevance, such as thresholds for energy audits or emissions certification. In addition to measuring technical outcomes, this study considers the ethical concerns, the role of local communities, and comparisons to global best practices. The findings highlight how artificial intelligence can meaningfully contribute to environmental conservation while also supporting sustainable economic development in maritime contexts. However, the analysis also reveals ongoing difficulties, particularly in areas such as ethical oversight, regulatory coherence, and the practical replication of successful initiatives across diverse regions. In response, this study outlines several practical steps forward: promoting AI-as-a-Service models to lower adoption barriers, piloting regulatory sandboxes within the EU to test innovative solutions safely, improving access to open-source platforms, and working toward common standards for the stewardship of marine environmental data.