It also speaks directly to the permission bottleneck Ellermann-Kingombe describes. Because data stays under the control of the nation or system that owns it, access can be governed by policy at the source, with classification boundaries and national rules enforced where the data lives rather than negotiated away in a central repository.
Rather than consolidating everything into a traditional data lake, a data mesh approach manages data where it originates and lives, without moving or duplicating it.
A data mesh approach is sustainable because of its reliance on open standards. They enable defense organizations to connect systems that were never designed to work together, from legacy platforms to dispersed infrastructure, so data stays findable and can be effectively analyzed across the environment. Interoperability stops being a barrier as new partners and data sources join, and new tools can be integrated without rebuilding systems or making major investments. The architecture scales alongside the Alliance’s growth.
Without a unified view, the risk of losing operational advantage to adversaries extends from the battlefield into cyberspace. Zero Trust depends on connecting authentication logs, network traffic and application telemetry where they already sit, so that traditionally separate domains can be visualized and analyzed together. When a user accesses sensitive data, the system must verify not only who they are but also their device status, network path, and the time and location of access. If those checks are slow or impossible, threats can remain undetected and escalate through systems. A data mesh built on open standards connects the pillars of a Zero Trust architecture, allowing organizations to accelerate implementation without replacing the tools they already have.
When the manual efforts of military data analysts struggle to keep pace with the scale and speed of events on the ground, AI can work faster and more accurately.
The same logic is already visible in large government organizations: CISA’s new SIEM-as-a-Service platform uses open standards to give US federal civilian agencies a consistent approach to threat detection and response.
As AI’s value in supporting human decision-making becomes increasingly clear, a data mesh architecture provides the foundation to apply agentic AI capabilities holistically. It enables complex organizations to analyze the vast amounts of data their systems generate, find actionable correlations and separate signals from noise. When the manual efforts of military data analysts struggle to keep pace with the scale and speed of events on the ground, AI can work faster and more accurately. It also lets analysts ask questions across structured and unstructured data and rapidly receive answers grounded in reliable sources.
The numerous tech challenges facing the modern military calls for closer NATO-industry cooperation, and that’s why NATO Edge 26 is such an important event. All 32 sovereign member states that make up the Alliance use different systems, yet they rely on secure, trusted data-sharing with each other as the foundation for cooperating on military operations and sharing intelligence. It’s vital that they can turn to industry innovators to support their operational needs.