Al Guber is the director of digital engineering/MBSE solutions architect at Arcfield
Artificial intelligence (AI) dominates defense headlines in 2026. It appears in budget justifications, acquisition reform conversations and modernization roadmaps. But AI is not the starting point for modernization. It is the accelerant. The real shift begins earlier.
Model-based systems engineering (MBSE) is reshaping how the Department of War (DOW) designs, builds and sustains mission systems. It does not attract the same attention as autonomous platforms or predictive analytics, yet it is foundational to both.
For decades defense programs relied on document-driven processes. Requirements were captured in static files. Engineering artifacts lived in separate systems. Integration and testing often occurred late in development when fixes were most expensive. That model struggles under today’s demands. Systems are increasingly software defined. Platforms must integrate across air, land, sea, space and cyber. Updates must occur in near-real time rather than months or years.
In 2025 the DOW reinforced its focus on digital modernization in its budget request and enterprise data guidance. Senior leaders emphasized interoperability, data visibility and faster acquisition pathways. These priorities reflect a clear understanding that legacy processes slow delivery and increase risk.
MBSE replaces disconnected documentation with integrated digital models that represent requirements, architecture, interfaces and performance in a shared environment. These models evolve throughout the life cycle of a system and create a common reference point for engineers, program managers and operators.
The results are tangible. When the Air Force developed the T-7A Red Hawk using a digital engineering approach it reduced software development time by 50% and cut assembly hours by 80%. Commercial sectors have reported cost savings of 25-30% and schedule reductions of up to 40% when model-based approaches are applied early. While defense programs vary in complexity the pattern is consistent. Digital engineering compresses timelines and reduces rework.
It also addresses a persistent government challenge. A large share of federal IT spending continues to support legacy maintenance. Systems that operate in silos limit visibility and complicate integration. In both 2025 and 2026 defense leaders have acknowledged that enterprise level data integration is essential to mission readiness. Digital threads that connect requirements, design, testing and sustainment data create traceability and strengthen accountability. They provide leaders with clearer insight into cost, schedule and performance tradeoffs.
For executives responsible for modernization portfolios this foundation matters. Oversight demands are increasing. Budgets are constrained. Near peer competitors are iterating quickly. Programs must move faster without sacrificing rigor. Digital engineering supports that balance by embedding transparency and discipline into the development process.
This is where the conversation must expand to AI. It is no longer possible to discuss modernization or innovation without discussing AI. In 2026 AI is embedded across defense planning documents and congressional testimony. Yet AI does not succeed in isolation. It depends on clean data, integrated architectures and clearly defined digital baselines. Organizations that attempt to deploy AI on fragmented legacy systems often discover that the constraint is not the algorithm. It is the infrastructure.
Once a program makes the transition from traditional processes to digital engineering the next step is expected. AI and automation become the natural accelerants. They can analyze model data, identify design tradeoffs, automate verification and support faster decision-making. Without a digital backbone those gains remain limited.
Modernization is not a single leap to AI. It is a sequence. Digital engineering builds the structure. AI drives the acceleration. Leaders who understand that progression will deliver capability faster and with less risk than those who pursue advanced analytics without first modernizing the foundation.