What happened
CSET (Georgetown) published a report examining practical applications of AI-enabled decision support systems (AI-DSS) beyond targeting, presenting two detailed case studies — Army ammunition resupply to fires units, and the Joint Air Tasking Cycle (JATC) — where AI-DSS could match the efficiency gains the XVIII Airborne Corps achieved with the Maven Smart System (accomplishing with a 20-person team what took 2,000 people in 2003). The report's central finding is that 'the primary obstacle to implementing suitable AI-DSS capabilities in these cases is not software development, but rather accessing the data needed by such tools,' much of which remains locked in unstructured formats like PowerPoint slides and unit-unique spreadsheets. It recommends CDAO prioritize making needed data digitally available, codifying DevSecOps best practices from the XVIII Airborne Corps, and deploying AI-DSS capabilities during real-world operations to build institutional expertise.
Why it matters
Identifies data-accessibility bureaucracy — not technology — as the binding constraint on scaling military AI decision support, a finding directly relevant to defense-sector technology executives and policymakers assessing AI procurement and data-governance investment priorities.
Action needed
Share with defense-sector business development and government-affairs leads assessing AI-DSS opportunities; flag data-accessibility barriers as a diligence item for AI vendor engagements with DoD.