Presented by EY
Jim Menard, Partner for Technology Transformation at EY, outlines a practical vision for artificial intelligence in the Defense Department that goes beyond experimentation and pilots. His call to action: adopt a “factory approach” that sustains and scales AI across missions.
“The Department of Defense is making exciting progress in back-office AI applications, like acquisition reform,” Menard said. These early wins often involve automating the compilation of solicitation documents, turning unstructured data into clean, actionable insights. But to move AI from the back office to the tactical edge, DOD needs a more holistic strategy.
Menard described a five-component factory model to guide this transformation. At the center are three core phases: demand management (to identify and prioritize use cases), execution (for development and deployment), and sustainment (to maintain and adapt solutions over time). Supporting those pillars are two foundational layers: AI-ready data and governance.
Without high-quality, secure, and ingestible data, AI cannot function effectively. “You can’t be AI-ready unless you’ve got ingestion-ready data,” Menard warned. Governance is equally critical—both to maintain AI systems and to ensure responsible, ethical use in alignment with risk management principles.
Menard noted that the DOD often stalls in the execution phase, failing to prioritize the most impactful use cases or to plan for long-term sustainment. The answer, he argued, lies in better front-end prioritization and clearer operating models that keep momentum going once the first prototypes are built.
He also emphasized the role of low-code and no-code development platforms in accelerating AI adoption. These platforms allow developers to build intuitive, visually designed applications using prebuilt components—saving time and money while enhancing user experience. “It really enables exceptional client or soldier experiences,” he said.
Finally, Menard pointed to adjacent industries like banking, financial services, and healthcare as models for how to leverage AI and low-code tools. “There are a lot of initial steps being taken that the DOD can learn an absolute ton from,” he said.
Key Takeaways:
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A “factory approach” with five pillars—demand, execution, sustainment, data readiness, and governance—can help DOD scale AI.
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Prioritizing high-value use cases and sustaining solutions beyond initial deployment are key to success.
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Low-code platforms and private-sector examples offer useful models for rapid, user-centered AI development.