FORT BELVOIR, Va. –
Approaching supply chain risk management with a proactive, data-centric mindset and artificial intelligence will ensure the Defense Logistics Agency provides stable warfighter support and reduces the impacts of supply chain disruptions, according to a new white paper.
The 14-page document, titled “Utilization of Artificial Intelligence to Illuminate Supply Chain Risk,” is written by DLA Chief Information Officer Adarryl Roberts.
DLA employees already use AI subsets like robotics and machine learning to support business processes and analyze metrics, but it can also help manage supply chain risks by predicting bottlenecks, forecasting customer demand, and recommending alternate, pre-qualified suppliers during disruptions, Roberts wrote.
The agency created the AI Center of Excellence in June 2024 to coordinate the safe and responsible integration of AI. DLA has since started using multiple risk assessment models to detect unreliable suppliers and ensure material meets customer specifications. Models are also being used to identify suppliers who provide counterfeit, non-conforming or overpriced items. Information from these AI-driven analyses can and has already been used to help prosecute vendors who jeopardize the supply chain, DOD missions and lives.
Roberts wrote that the success of DLA’s models could make them a possible solution for broader supply chain risk management initiatives throughout DOD.
“DLA’s efforts showcase how AI-driven analytics enhance accountability, streamline investigations and preempt supply chain threats,” he continued, adding that DLA’s AI models are key to protecting warfighters and ensuring national defense operations are fueled by reliable, compliant suppliers.
Another AI model in use at DLA Aviation identifies areas where the agency can take more risks by ordering higher quantities, thereby increasing supplier interest and ensuring supplies are always on hand. That also helps suppliers better invest in resources and infrastructure for future demands, Roberts wrote.
“The model’s real-time dashboard lets suppliers adjust, helping them stay responsive to shifting battlefield conditions and new threats,” he continued. “Cutting waste and synching procurement with actual demand makes better use of defense budgets, freeing up resources for advanced tech and increasing readiness.”
The paper highlights studies by the Government Accountability Office and Defense Department Inspector General that reveal vulnerabilities in stockpile management and oversight of Defense Fuel Support Points. Regarding inventory, AI monitoring systems can help track critical materials as they move through the supply chain from mining and processing to incorporation in military systems.
Gaps also exist in data for some DLA-managed strategic materials, hindering the ability to assess risks and plan for contingencies. But AI can enable the agency to overcome data limitations by aggregating information from multiple sources to create a unified view of the supply chain and an accurate picture of stockpile requirements.
In managing fuel support points, AI-powered drones and advanced sensors can reduce or eliminate the need for in-person inspections.
“These tools provide real-time monitoring, enabling early identification of structural weaknesses or environmental hazards,” Roberts wrote. They can also enhance the reliability and frequency of monitoring and improve predictive maintenance.
The paper is available on DLA's Campaign of Learning webpage (DLA common access card required), which features additional white papers and a curated reading list on supply chain management, history, emotional intelligence and more.