FORT BELVOIR, Va. –
Artificial intelligence is already empowering decisions across the Defense Logistics Agency with over 55 models in various stages of production, testing and use in areas like demand planning and supply chain risk management. Over 200 use cases are also exploring the power of AI to increase efficiency and analyze agency data.
AI adoption is expected to continue growing as DLA Information Operations’ AI Center of Excellence, created in June 2024, provides oversight and governance for exploring how AI tools and technologies can improve processes, said Ruksana Lodi, DLA’s AI officer. In addition to tracking all AI inventory throughout DLA, her team is establishing AI guidance, prioritizing use cases that further DLA’s strategic goals, standardizing processes and more. A cohesive approach is key.
“If you go out and find a tool on your own and buy it, and then I do the same, we would end up with many tools that may have the same functionality,” she said. Instead, the team is streamlining the agency’s use of AI to create a unified AI ecosystem that’s efficient and cost effective without duplication.
The shared functionality that Lodi’s team aims for ensures systems and processes throughout DLA are interoperable, especially when it comes to tasks such as measuring success and applying predictive analytics across multiple supply chains. Although end users and subject matter experts determine how AI is used to support specific DLA operations, the team makes sure AI is integrated safely and responsibly.
“The goal is to ensure that AI-driven decisions don’t compromise security, quality or operational efficiency, ultimately protecting both the agency and the warfighter,” Lodi said.
Since some AI tools rely on cloud-based processing, DLA must also adopt practices that prevent unauthorized access, service outages, latency issues and potential breaches, she added.
DLA Director Army Lt. Gen. Mark Simerly prioritized strengthening digital interoperability and developing AI-powered solutions in the agency's 2025-2030 Strategic Plan. Tools like predictive analytics are expected to help the agency deliver more timely results and better outcomes.
They can also help employees plan smarter, faster logistics support by eliminating guesswork, Lodi said.
“For example, AI can be used to prevent stockouts and overstocking,” she said. “This keeps supplies available when needed, avoids delays and reduces inventory costs.”
AI already improving processes
DLA began identifying potential use cases in the summer of 2018 and found 26 processes that could be improved by AI and machine learning, including inventory reconciliation and data analysis of areas like pricing, performance and delivery. By the fall of 2018, the agency introduced its first AI tool, a virtual assistant known as Val, to help employees solve IT issues. Like most AI models, the more employees used it, the better its answers became. And newer technology is already replacing previous tools like Val.
In business decision analytics, Lodi’s team is tracking a collection of models that perform tasks like assessing supplier risks. One tool automates the identification of vendors that could potentially supply counterfeit or overpriced items by looking at supplier behaviors, past performance and fraudulent activity patterns. Such assessments helps DLA avoid unreliable vendors and reduce the chances of defective parts being used on critical defense systems, Lodi added.
Another AI model that focuses on long-term contracts at DLA Aviation identifies where the agency can take more risks by ordering higher quantities, thereby increasing suppliers’ interest in working with the government and strengthening the nation’s defense industrial base.
In DLA Finance, AI may even help the agency achieve a clean financial audit. Shawn Lennon, DLA’s deputy chief financial officer, announced in November that his team is looking at using AI for time-consuming tasks like reconciling financial records with inventory in the Warehouse Management System.
“Today, we’ve got many people manually reviewing error transactions, trying to figure out what went wrong, why and the potential solution,” he said. “It’s too much for us to keep up with.”
AI can additionally help finance experts detect errors, generate insights, and propose solutions to improve data quality and financial reporting, Lennon added.
The agency also awarded three contracts in November to support exploration of AI tools that will create reporting mechanisms for demand planning use cases, a customized chatbot app and virtual agents for acquisition business systems.
Incorporating such AI assets in DLA’s business practices shows the agency is in lockstep with the private sector in harnessing emerging technology, Lodi said.
"Our director's focus is on ensuring we're ready, proactive and agile in this contested logistics environment, and the way to do that is to stay on par with industry and our competitors in terms of technology," she said. "If we don't, we'll be left behind."
Ensuring employees know how to interpret data and apply algorithms to improve programs and processes is also crucial to reaping the benefits of AI.
“This is all part of our data acumen training as we help employees gain knowledge beyond building AI tools so they can use them more efficiently and effectively to make DLA more successful in its mission,” Lodi said.
More information about DLA’s focus on digital interoperability, data analytics and AI is available for common access card holders on the Campaign of Learning webpage.