Digital transformation in defense is often discussed through technology: AI-enabled decision support, predictive maintenance, digital twins, secure data sharing, automation, and interoperable systems. These capabilities are important, but none of them execute themselves.
In practice, many defense and aerospace organizations are trying to modernize while the people responsible for execution are already under pressure. Maintenance teams are managing aging assets. Engineers are supporting long-life programs. Skilled trades are in short supply. IT and security teams are balancing modernization with strict control requirements. Planners and operational teams are still reconciling work across spreadsheets, email, SharePoint, legacy databases, and systems that were never designed around daily execution.
That creates a hidden workforce crisis behind defense digital transformation. The issue is not only whether organizations can buy or build new technology. It is whether they have the workforce capacity, digital literacy, and knowledge continuity needed to turn that technology into better readiness, sustainment, and asset lifecycle performance.
A 2025 PwC article on the aerospace, space, and defense workforce describes a sector facing a generational transition, where retirements threaten to remove vital unwritten knowledge from long-life programs. The 2025 Aerospace Industries Association (AIA) and McKinsey workforce study similarly points to persistent attrition, critical skill gaps, and the need to unlock more productivity from the workforce already in place. McKinsey’s own research on the A&D talent gap connects workforce shortages to hiring speed, retention, time to proficiency, and operational performance.
Digital transformation cannot depend only on data scientists, software engineers, or central IT teams. Defense organizations also need digital confidence across the people who plan, execute, inspect, maintain, document, approve, and hand over work.
A maintainer does not need to become a data engineer to support predictive maintenance. But they do need systems that make it easy to capture accurate maintenance actions, asset condition, part usage, exceptions, and decisions at the point of work. A planner does not need to build AI models. But they do need to understand how data quality affects future planning, readiness reporting, and decision support.
Boston Consultancy Group makes a similar point in its article on building digital and AI skills at scale in defense. Defense organizations are making large investments in digital technology and AI, but those investments need to be matched by skills development among armed forces personnel and civil servants who must use these capabilities in the mission environment.
Skills England’s 2025 defense skills assessment shows why this is broader than software talent. Employers identified gaps across craft skills, specialist skills, and new skills such as digital, cyber, and green. In asset-heavy environments, those categories are connected. Digital transformation depends on both the people who understand the asset and the people who understand the data.
Defense modernization still depends on welders, electricians, aircraft maintenance technicians, fitters, engineers, quality teams, and production specialists. These roles are not separate from digital transformation. They are where much of the operational data begins.
If frontline execution is inconsistent, digital systems inherit inconsistent records. If maintenance work is documented after the fact, data loses context. If skilled workers rely on personal notes, informal workarounds, and undocumented experience, digital tools cannot easily convert that knowledge into reusable organizational intelligence.
The 2025 AIA and McKinsey workforce study found that A&D companies continue to face hiring challenges in engineering, skilled manufacturing, and software engineering. That combination is important. The workforce shortage is not only a technology labor problem. It is a delivery problem across the entire asset lifecycle.
The pressure is especially visible in skilled trades, where scarce talent is often asked to absorb both operational work and administrative friction. See Why Skilled Trades Are the Bottleneck in Defence Modernization.
Experienced workers often hold practical knowledge that does not appear in formal documentation. They know which assets behave differently under certain conditions, where delays usually begin, how specific suppliers work, what exceptions require escalation, and which shortcuts create risk.
When that knowledge stays in people’s heads, digital transformation becomes fragile. The organization may digitize a form, a report, or a maintenance record, but the reasoning behind the work remains undocumented. When experienced workers retire or leave, the system may preserve the record of what happened without preserving the knowledge needed to understand why.
PwC highlights this risk in long-life aerospace and defense programs, where expertise can take many years to build and where project lifecycles may stretch across decades. The loss of experienced professionals creates knowledge gaps that are difficult to fill quickly, especially when knowledge transfer is informal or delayed.
For a deeper look at how maintenance knowledge disappears during turnover and retirement, see Why Maintenance Knowledge Walks Out the Door.
The workforce transition from experienced “gray” employees to newer “green” employees changes the requirements for digital systems. Older workers may be cautious about new tools if they feel slower, less secure, or disconnected from how work actually happens. Younger workers may expect clearer interfaces, guided workflows, faster feedback, and less dependence on paper-heavy or spreadsheet-heavy processes.
The answer is not to blame either group. The real issue is whether the organization has converted individual expertise into structured, usable workflows that new teams can follow and improve.
McKinsey’s work on the A&D talent gap points to the difficulty of transferring knowledge from tenured employees to newer employees, especially as the sector gets younger and experienced managers leave. This is part of the broader The Grey-to-Green Transition in Aerospace and Defence, where incoming workers inherit both long-life assets and the process debt built around them.
Workforce shortages become worse when skilled people spend too much time searching for information, reconciling spreadsheets, chasing approvals, duplicating data entry, proving that work was done, or trying to understand who owns the next action.
In many defense and complex asset environments, the real workflow still lives across email threads, Excel files, SharePoint folders, old databases, local documents, and individual memory. These tools may feel familiar, but they consume attention and make accountability harder. They also make it difficult to create a reliable digital trail across maintenance, assembly, deployment, sustainment, and support.
Our internal delivery experience with defense and complex asset organizations shows how common this pattern is. Teams often want better automation, reminders, task ownership, access control, and overview, but the existing workflow is scattered across tools that were never designed to govern operational execution.
The AIA and McKinsey workforce study argues that A&D organizations need to rethink how work is designed and executed, not only recruit more people. That point is critical. If scarce talent remains trapped in low-value coordination work, digital transformation adds pressure instead of capacity.
Many defense organizations do not have a technology adoption problem first. They have a workflow fit problem.
Systems fail when they are designed around administration, reporting, or compliance but do not match the sequence of operational work. ERP, PLM, MES, and other enterprise systems remain important, but they are not always built for frontline execution. A system of record can store asset information without making maintenance, assembly, or sustainment work easier to perform.
Digital adoption improves when systems reduce friction. That means clear task ownership, guided steps, role-based access, automatic traceability, usable handovers, and workflows that reflect how maintainers, fitters, planners, engineers, and support teams actually work.
In this sense, workforce enablement is not a soft change-management issue. It is a design requirement. Defense teams need digital workflows that make the work easier to do correctly, not just easier to report on later.
Predictive maintenance, AI-enabled planning, digital twins, and lifecycle analytics all depend on reliable operational data. But data quality is not created by dashboards. It is created when work is captured consistently, close to where it happens, with enough context to be useful later.
The United States Government Accountability Office’s report on Department of Defense AI workforce management is a useful reminder that AI readiness is not only a technology investment issue. DOD has invested heavily in AI, but GAO found that workforce management practices still needed improvement, including clearer identification and management of the AI workforce.
That lesson applies beyond AI specialists. If defense organizations want better insight from asset data, the broader workforce needs enough digital literacy to understand why accurate, structured data capture matters. Poor maintenance records weaken predictive models. Incomplete handovers weaken planning. Unstructured notes weaken auditability. Missing asset context weakens lifecycle decisions.
Defense organizations have legitimate security requirements. Data ownership, access control, deployment environment, auditability, and sovereignty all matter. But security concerns can also lead teams to preserve manual processes that feel safer than they really are.
Email and spreadsheets can create a sense of control because users know where the file is and who they sent it to. In practice, these tools can increase risk through accidental sharing, version confusion, corrupted files, inconsistent access, and weak accountability. The safer long-term approach is not to avoid digital workflows. It is to design them around controlled access, clear ownership, secure data handling, and traceability from the start.
This is where secure asset data-flow thinking becomes important. Tools such as Empact Connect are designed around the principle that defense organizations should be able to move asset data securely without giving up control, ownership, or existing infrastructure. The broader point is simple: security should shape the workflow, not freeze it in manual workarounds.
A successful defense digital transformation should reduce manual coordination, preserve operational knowledge, guide execution, make accountability clear, support secure data capture, and give frontline users a practical reason to adopt the system.
That means workforce enablement should be treated as core infrastructure. Training matters, but training alone cannot fix a workflow that is poorly designed. Hiring matters, but hiring alone cannot fix processes that waste skilled time. AI and automation matter, but they cannot create value from inconsistent, missing, or untrusted operational data.
Organizations that want to preserve expertise need more than exit interviews. They need structured ways to capture, validate, and reuse operational knowledge. See How to Capture Tacit Knowledge Before Experienced Workers Retire.
The next phase of defense digital transformation will be judged by execution. Can the organization capture knowledge before it leaves? Can new workers become productive faster? Can maintainers and planners trust the data they use? Can digital systems reduce administrative burden instead of adding another layer of reporting? Can secure workflows support real operational conditions?
For complex asset organizations, asset lifecycle software can help bridge the gap between systems, people, and processes. By bringing together operational knowledge, asset data, and day-to-day workflows, it creates a more connected and structured way of working. The goal is not to introduce another layer of technology, but to make work easier to execute by giving teams better visibility, clearer responsibilities, and fewer manual tasks.
Defense organizations do not only need better technology. They need workflows that help scarce, experienced, and digitally stretched teams perform under pressure. For a broader framework on preserving operational knowledge across teams, assets, and lifecycle stages, see The Knowledge Continuity Playbook for Asset-Heavy Organizations.
This challenge is also part of the wider The Workforce and Knowledge Continuity Crisis in Asset-Heavy Industries, affecting organizations that depend on experienced workers, long asset lifecycles, and operational knowledge that is difficult to replace.