AI and data analytics for sustainability: A strategic framework for risk management in energy and business

This paper explores the integration of artificial intelligence (AI) and data analytics in promoting sustainability and enhancing risk management within the energy and business sectors. It highlights the role of AI technologies in driving energy efficiency and sustainable practices, demonstrating how predictive analytics can optimize energy usage and integrate renewable energy sources. The significance of data analytics in risk mitigation and strategic planning is discussed, showcasing its capacity to provide data-driven insights for proactive risk management. Furthermore, the paper outlines AI-driven models for predictive analytics in energy systems, emphasizing their benefits in forecasting, operational optimization, and sustainability. Recommendations for implementing AI and data analytics in sustainability initiatives are provided, focusing on investment in data infrastructure, fostering a data-driven culture, scalable solutions, interdisciplinary collaboration, ethical practices, and regulatory compliance. The paper concludes by underscoring the transformative potential of AI and data analytics in achieving sustainability goals and improving resilience in the energy and business sectors.