The defence data problem isn't a lack of information
For decades, defence organizations have invested heavily in gathering information. More sensors, more satellites, more intelligence feeds, more surveillance systems. Success was often measured by increasing collection capability.
Today, while new sensors are still being adopted, that challenge has been solved and a new one raised.
Modern militaries are surrounded by data. Intelligence feeds stream continuously from land, sea, air, cyber and space domains. Unmanned systems generate vast quantities of video and sensor information. Open-source intelligence adds another layer of complexity, while cyber monitoring tools create a constant flow of alerts and indicators.
The problem facing defence leaders is no longer how to collect more information — the problem is how to make sense of what they already have.
While many discussions focus on software architectures, interoperability and technology modernization, the real opportunity is much simpler: helping defence organizations turn data into decisions faster. One aspect of software-defined defence (SDD) that will help is data centricity.
More data does not automatically create better decisions
A common misconception is that more data leads to better outcomes. In reality, increasing amounts of information can have the opposite effect.
Analysts and commanders often face an overwhelming volume of reports, imagery, sensor feeds and intelligence products. Critical details can become buried within thousands of other data points competing for attention.
The challenge is often described through three characteristics of modern defence data:
Volume: there is too much of it
Velocity: it arrives too quickly
Veracity: its quality and reliability can vary significantly
Even highly trained personnel struggle to keep pace when information arrives faster than it can be assessed. The result is a growing risk that valuable intelligence is overlooked, delayed or never fully exploited.
In modern operations, the organization that understands first often gains the advantage. The organization that identifies valuable information too late will have fewer options on how to act.
Why data centricity matters
One of the core principles of SDD is to be data centric by design.
Traditionally, defence organizations have built processes around applications and systems. Information becomes associated with the software that created it, stored it or analyzed it. Over time, this has created silos of data and of knowledge.
Information is duplicated across multiple systems. Different teams work from different versions of the same dataset. Valuable intelligence exists somewhere within the organization but remains difficult to discover or access.
A data-centric approach reverses this model. Instead of treating applications as the center of the ecosystem, data becomes the central asset. Software tools become enablers that access, analyze and exploit information. Data does not need to be centrally stored (a bad idea in defence resilience), but it can be connected and viewed as one repository. Whether it’s tactical, strategic, current or two weeks old, data is relevant to users at the time of need for multiple use cases.
The distinction may sound subtle, but it has significant operational implications. When data is treated as a strategic asset, organizations become more agile. New applications can be introduced without moving data. Existing systems can be upgraded without disrupting information flows. Analysts can focus on extracting value rather than searching for information.
Most importantly, data becomes easier to share across teams, allies and operational domains.
Breaking the cycle of data silos
Is there a defence organization that has not experienced the frustration of data silos?
A valuable dataset exists, but another department cannot access it. Information collected for one mission remains isolated from broader operational analysis. Multiple groups unknowingly create duplicate versions of the same information.
These challenges are not new, but they become more significant as data volumes continue to increase. SDD helps address this problem through open architectures, common standards and centralized data management approaches. Rather than asking users to navigate dozens of different systems, the objective is to create a shared information environment where data can be discovered, trusted and reused.
This produces benefits that extend far beyond efficiency. Intelligence can be fused more effectively. Collaboration improves. Decision-makers gain a more complete operational picture. Resources that were once spent managing information can instead be focused on understanding it.
Why metadata is more important than most people realize
The value of data depends heavily on context. A drone image, for example, may be highly valuable, but only if analysts know when it was captured, where it originated, what sensor collected it and how dependable the source is.
This contextual information is known as metadata. Often described as "data about data," metadata provides the foundation for discovery, validation and trust. Without it, even high-quality intelligence can become difficult to use.
As data volumes increase, manually maintaining metadata becomes impractical. Software-defined environments increasingly automate metadata capture, validation and harmonization. This ensures information remains searchable, accessible and reliable across large organizations. While metadata rarely receives the same attention as artificial intelligence or advanced analytics, it is one of the most important enablers of effective data exploitation. Without it, the other actions cannot occur.
The practical role of AI in defence
Artificial intelligence is frequently portrayed as a revolutionary technology that will transform warfare overnight.
The reality is more practical. The differing types of AI models, such as machine learning, generative, unsupervised and large language, are only as good as their training. A model must be applied to data it “knows about.” For instance, if the training data is imagery of tanks in a wintery forest setting, do not expect the AI model to recognize tanks in a desert. For most defence organizations, the immediate value of AI lies in helping personnel manage information overload.
AI can assist by:
Identifying patterns across large datasets
Highlighting anomalies that may warrant investigation
Prioritizing information for analysts
Supporting automated processing workflows
Accelerating intelligence production
In each case, the goal is not to replace human expertise. The goal is to help analysts and operators work more effectively.
When AI identifies a potential threat hidden within thousands of hours of surveillance footage, human judgment remains essential. The difference is that analysts can focus their attention on what matters most rather than manually reviewing every piece of data. This is where AI delivers measurable operational value today.
From data collection to decision advantage
The ultimate objective of SDD is not better processes. It is better decisions.
Every sensor, data platform and analytics capability exists to support operational understanding and informed action. By automating data workflows, reducing information silos, improving accessibility and applying AI where appropriate, organizations can significantly shorten the time between data collection and decision-making. This becomes increasingly important as operational environments become more complex and adversaries move more quickly.
The challenge is no longer obtaining information. The challenge is extracting insight before the opportunity to act disappears.
The future belongs to organizations that can exploit data faster
Defence organizations have invested heavily in sensors and information collection capabilities. The next competitive advantage will come from how effectively they exploit the data they already possess. Recent campaigns have shown that nations are already using AI to suggest target lists, running into thousands of targets.
SDD provides a framework for achieving that objective. By placing data at the center of operations, embracing interoperability and using automation and AI to accelerate workflows, defence organizations can convert overwhelming volumes of data into actionable intelligence. The battlespace will reward those who can understand, adapt and decide fastest.