The growing complexity and volume of space operations necessitate advanced analytical capabilities to ensure mission effectiveness and safety. The U.S. Space Force faces significant challenges in prioritizing sensor observations, scaling analysis to a vast number of resident space objects, and understanding the intricacies of orbital mechanics. This report investigates the potential impact of Artificial Intelligence (AI) and Machine Learning (ML) tools on Space Domain Awareness (SDA), focusing on enhancing analysis tempo, expanding usable data, and freeing operators for complex tasks. The primary objective is to characterize the nature of this impact, particularly within the conjunction assessment process for quantifying collision risk, thereby addressing a critical gap in understanding that hinders effective integration planning.

This report is positioned as a critical assessment for understanding the integration of AI/ML into Space Domain Awareness operations. By detailing the potential benefits and challenges, it aims to inform planning and strategy within the U.S. Space Force. The methodology, which includes stakeholder interviews and model development, suggests a practical and data-driven approach to evaluating these advanced technologies. The work directly addresses a recognized gap in understanding the impact of AI/ML on mission effectiveness, particularly concerning collision risk assessment.