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AI's ability to process large data sets and make intelligent decisions has revolutionized the industrial landscape and opened new avenues for innovations that can contribute to a more sustainable future. It plays a pivotal role as a catalyst for digital transformation, particularly in sectors such as energy production, where it offers significant potential to promote sustainable development. This study researches the factors that condition artificial intelligence (AI) implementation in the energy sector based on the Technological-Organizational-Environmental (TOE) framework. It employs a deductive approach to identify AI implementation's technological, organizational, and environmental factors through a qualitative case study approach involving an energy company in Sweden. Our findings indicate that technological readiness and organizational alignment are essential, with differences in environmental pressures further affecting AI readiness. The study concludes that successful AI implementation depends on robust technological structure and organizational readiness, with varying environmental factors regulating these conditions. This research contributes to the literature by emphasizing the critical role of AI readiness in optimizing operations and driving innovation within the energy sector, accentuating the need for companies to enhance their AI capabilities to manage integration challenges effectively. This study enriches the TOE framework by introducing an additional dimension to the environmental factor, incorporating Network considerations where boundaries are undefined due to digitalization.