This thesis investigates the integration of artificial intelligence (AI) into the Swedish electricity sector, focusing on enhancing operational efficiency and business value creation. With forecasts predicting a doubling of Sweden's electricity consumption by 2045 and the recent surge in AI applications, this research explores whether AI can help mitigate challenges arising from increased electricity consumption. Sweden's transition to weather-dependent renewable energy sources places higher demands on the functionality of its electrical grid, established in the early 20th century, which now requires significant upgrades. Using the Technology-Organizational-Environmental (TOE) framework, the study examines key aspects of AI integration. A qualitative methodology, employing Grounded Theory, gathers insights through iterative interviews with key actors in the AI and Swedish electricity sectors. Findings indicate that AI has the potential to optimize energy management, improve grid stability, and support the transition to renewable energy sources within the Swedish electricity sector. However, challenges such as cybersecurity, data management, and regulatory compliance are significant. The study concludes with strategic recommendations for AI integration, emphasizing the importance of robust data infrastructure, skilled personnel, and adaptive regulatory frameworks to integrate AI into the Swedish electricity sector and create business value. Moreover, transparency and education are highlighted as crucial for building public trust and ensuring that AI enhances human capabilities. / <p>Tomas var examinator för Teknisk Fysik där Alexander var teknisk ämnesgranskare. Carla var examinator för Energisystem där Rafael var teknisk ämnesgranskare. Arbetet skrevs med Entreprenörsskolan på Uppsala Universitet där Matthew var ämnesgranskare.</p>