Executive Summary
This integrated research project explores the integration of artificial intelligence (AI) and machine learning (ML) technologies into the Joint Force planning processes, specifically focusing on enhancing the common operational picture (COP) and course of action (COA) development within the Joint planning process. By examining the technical, organizational, resource, and ethical dimensions of AI/ML adoption, the study identifies opportunities to optimize situational awareness and decision making.
These AI/ML technologies can process vast amounts of data, streamline planning tasks, and provide actionable insights while emphasizing the necessity for robust data acquisition, structuring, and curation practices. Organizational impacts, including shifts in roles, division of labor, and the incorporation of external vendors, are examined alongside the challenges of resource demands and sustainability under operational constraints. Ethical considerations and adherence to principles of responsible AI are integrated throughout the analysis to ensure alignment with societal values and military standards.
The research employs unstructured interviews and secondary data reviews to evaluate top-down and bottom-up efforts to incorporate AI/ML technologies. It identifies barriers to successful integration, such as data standardization, access across classification levels, and aligning organizational practices with emerging technologies. The findings underscore the importance of a centralized yet adaptable framework to address these challenges and provide actionable recommendations for advancing AI/ML capabilities in military planning. This study contributes to the broader effort of leveraging AI/ML to maintain a strategic advantage, offering insights into developing, applying, and optimizing these technologies within complex and dynamic military contexts.