Miles Jamison 
- The War Department’s AI Acceleration Strategy is backed by fiscal 2026 NDAA funding
- ITC Federal’s Zhenia Klevitsky said fragmented data environments remain a major obstacle to wider AI adoption
- Klevitsky also said legacy technology infrastructure continues to complicate AI integration efforts
The Department of War’s effort to operationalize artificial intelligence hinges on addressing longstanding data access, security and governance challenges tied to legacy systems, according to Zhenia Klevitsky, chief growth officer of ITC Federal.
In an Aug. 3 Defense Opinion article, Klevitsky said the department’s AI Acceleration Strategy seeks to transition AI initiatives from experimentation to operational use, supported by significant funding in the fiscal 2026 National Defense Authorization Act for AI adoption efforts.
What Challenges Does the DOW Face in Scaling AI?
Klevitsky said obstacles to broader AI deployment include data systems that remain siloed, are inconsistently labeled and are difficult to access in real time. She also pointed to challenges in integrating AI into legacy systems that are not designed for such technologies.
The ITC Federal executive further cited evolving security architectures and governance frameworks that have not kept pace with AI acquisition and deployment activities. She also mentioned that accountability, ethical standards and approval processes remain fragmented.
What Steps Could Help Accelerate AI Deployment?
According to Klevitsky, the War Department should first establish a common enterprise architecture built on shared standards to support secure data access within domains and classification levels. She also recommended centralized AI governance bodies with operational authority to oversee standards, reduce duplicative work and align investments with departmental objectives.
Klevitsky also recommended mandatory AI literacy training for leaders, cross-functional collaboration among operators and acquisition professionals and career incentives that encourage AI proficiency. She added that human oversight should focus on critical decisions while allowing autonomous systems to operate within defined parameters during time-sensitive missions.
