AI-Driven Strategic Management and Decision Making for Energy Sector

Abstract

The energy sector faces unprecedented challenges, including volatile market conditions, fluctuating resource availability, and the urgent need for sustainable energy transition. Artificial intelligence (AI) offers transformative potential in addressing these challenges by enhancing strategic management and decision-making processes. This research explores the integration of AI-driven tools and methodologies into strategic management practices in the energy sector, focusing on optimization, predictive analytics, and automated decision systems. By leveraging machine learning, neural networks, and data-driven modeling, AI can provide actionable insights for supply chain optimization, demand forecasting, risk assessment, and sustainability planning. This study examines real-world case studies and employs econometric and computational models to evaluate the effectiveness of AI applications in improving operational efficiency, cost-effectiveness, and environmental outcomes. Additionally, the research investigates the ethical implications, regulatory considerations, and barriers to AI adoption in this critical sector. The findings aim to guide energy companies in aligning AI-driven strategies with long-term goals, fostering innovation, and promoting resilience in an evolving global energy landscape.