The upstream oil and gas industry faces unprecedented challenges, including operational complexity, environmental regulations, and volatile market conditions. Artificial intelligence (AI) emerges as a transformative technology capable of addressing these multifaceted challenges through enhanced decision-making, predictive analytics, and automated monitoring systems. This chapter examines the implementation of AI across upstream operations, encompassing subsurface modeling, drilling optimization, environmental monitoring, and safety enhancement. We demonstrate how AI technologies are reshaping traditional workflows by analyzing real-world applications, including production forecasting, emissions detection, and intelligent automation systems. The chapter explores machine learning applications in type curve analysis, real-time drilling optimization, carbon capture monitoring, and methane leak detection. Additionally, we examine the integration of large language models for knowledge management and the deployment of edge computing solutions for autonomous field operations. Environmental applications receive particular attention, highlighting AI’s role in emissions reduction, regulatory compliance, and sustainability reporting. We will discuss emerging trends, including digital twins, federated learning, and autonomous operations that will define the industry’s technological evolution. The findings indicate that AI adoption in upstream operations not only improves operational efficiency by 15–30% but also enhances safety protocols and environmental compliance, positioning the industry toward more sustainable and intelligent operations.