AI and additive manufacturing (AM) are a powerful combination with the potential to accelerate the adoption of AM across industries. AM excels at producing complex geometries with minimal waste, agile supply chains, and shorter lead times. However, its broader adoption is constrained by high costs and persistent challenges in quality assurance. AM processes are highly sensitive to variables such as environmental conditions, material properties, machine variability, and design complexity. At the same time, AM is inherently data-rich—making it ideal for AI-driven insights. For example, AI can monitor the build process in real time, detect anomalies, and assess their impact on part quality as each layer is formed. In this webinar, we will explore AM applications in the oil and gas sector, discuss the root causes of quality variability, and share how we are leveraging AI to enable real-time monitoring and improved process control.