Research Highlight: Optimized Portfolio Digital Engineering Transformation

Dec 15, 2025

The SERC portfolio of funded research tasks furthers its guiding vision of being the networked national resource to further systems research and its impact on issues of national and global significance.

Research Highlight

Research Task: Optimized Portfolio Digital Engineering Transformation
Sponsor: National Nuclear Security Administration, Office of Systems Engineering & Integration
Principal Investigator (PI): Dr. Paul Wach (University of Arizona, formerly with Virginia Tech)
Co-PIs: Dr. Taylan Topcu and Dr. Kelli Esser (both Virginia Tech)
Key Contributors: Dr. Nicole Hutchison and Mr. Nicolas Jurczyk (both Virginia Tech)

Read the final technical report

To keep pace with accelerating technological change, defense acquisition needs to shift to a seamless environment where systems data and models are authoritative, reusable, and shared across the lifecycle. Current practices are based on human expertise and document-driven processes, which lead to inefficiencies, rework, schedule and cost overruns. It is critical to evolve toward dynamic, context-aware, model-based, and artificial intelligence (AI)-assisted methods.

“The transformation referred to as digital engineering took many in the national security industry by surprise and has yet to realize the purported benefits. Many remain in transformation phase zero, where siloes are still strong and documents (e.g., PPTs) are still the main form of exchange. By taking a research path that seeks disruption, we give industry the opportunity to see beyond the horizon.”
– Dr. Paul Wach, PI

Purpose

The Optimized Portfolio Digital Engineering Transformation began with a focus on assisting the sponsor in its current transformation and evolved as the true need was uncovered: get ahead of the next transformation.

Task Overview

Develop a transformation framework
Assess the current state (circa 2025), future state (circa 2035), and potential steps in between (e.g., 2028, 2032)
Synthesize actionable recommendations for transformation of systems engineering methods, infrastructure, and workforce

“Most engineering organizations are consumed with navigating the digital engineering (DE) transformation, overlooking its potential to revolutionize how we develop and sustain complex engineered systems. This collaboration explores a reimagined approach to systems engineering—one that leverages DE and AI synergistically to enable better, faster, and more cost-effective system development in a trustworthy manner.”
– Dr. Taylan Topcu, Co-PI

Recommendations to Prepare for Systems Engineering in 2035

Aside from the need to holistically consider capabilities, actionable recommendations included:

Prioritize agentic AI. Invest in the development, validation, and deployment of agentic AI systems that actively reason and adapt, with human-in-the-loop to ensure mission assurance.
Embed governance early. Establish policies for data provenance, model ownership, and data lifecycle continuity for future contextualization and cross-boundary learning. Treat governance as an enabler rather than a constraint.
Pilot now, scale later. Launch structured pilot programs and sandbox environments to test AI-driven requirement specification and DE tools under controlled conditions, with embedded verification and validation. Accelerate workforce adaptation in these safe environments.
Define success metrics. Move beyond narrow efficiency metrics, such as value metrics. Set organization-wide success metrics to track adaptability, resilience, trustworthiness, and mission alignment across programs.
Strengthen security and cyber resilience. Seek secure-by-design practices and adaptive, resilient architectures with recovery mechanisms to ensure continuity of operations.

“True transformation isn’t about adopting the newest tools. It’s about preparing the people to operate differently. By mapping the future state now, we give organizations the clarity they need to build competency, confidence, and momentum before disruption arrives and to respond to it in an agile manner.”
– Dr. Nicole Hutchison, Key Contributor

Consistent trends suggest that:

AI will be inherently embedded in all facets of systems engineering
Humans will continue to be valued through human-machine teaming
Methods are expected to evolve to compensate for data storage needs
XR and other wearable sensory tech will spread in use
Additive manufacturing will provide early prototype capabilities and rapid manufacturing

“Not only do we get to explore the cutting-edge technologies shaping digital engineering today, we have the opportunity to make meaningful contributions to what the future of systems engineering will look like.”
– Nicholas Jurczyk, PhD Candidate and Key Contributor

Next Steps

The success of and interest in this task has resulted in follow-on work. Over the course of the next three years, the research team seeks disruption through an iterative approach.

Create exemplars and plans to transition the technology to industry
Create a Sandbox that is representative of industry
Shape the vision and roadmap to proactively transform systems engineering

In the next phase of this project, the research team has initiated WRT-2516, referred to as: “Systems Engineering Beyond the Horizon.”