How national security within global ecosystems offers a model for the commercial AI world

Rethinking ecosystems when the national interest comes first

Business leaders have long been comfortable thinking in terms of “ecosystems”: networks of partners, platforms, and customers that create value together. In the last decade of the 20^th century and the first two decades of the 21^st century, the implicit picture was a single global web. Today, that vision of a unified global ecosystem is breaking down. Around critical technologies, infrastructure, and resources in particular, we are seeing the emergence of new ecosystems based on national and regional interests. Ports and logistics hubs, energy grids, semiconductor fabs and AI chips, cloud and telecoms infrastructure, and key materials are no longer being treated simply as commercial assets; they are increasingly viewed as key components in national security policies and industrial development strategies.

For multinationals, especially in strategically sensitive sectors such as energy, finance, and technology, this shift is no longer abstract. While global supply chains and international customer bases remain, businesses increasingly find themselves belonging to a set of national or bloc-based systems with hard edges. China’s dominance in rare earths, concerns about over-reliance on Taiwan’s semiconductor industry, conflicts over access to COVID-era vaccines, and U.S. restrictions on high-end chip sales to competitors have all made one point clear. Questions such as “Which government has the right to guide and limit our actions?” and “Where do we really belong?” are now returning to the foreground of business strategy. In practical terms, many companies will find that they cannot remain equally embedded everywhere. They will be expected to deepen their ties in some jurisdictions, loosen them in others, and, in certain parts of their business, make an explicit choice about whose rules and priorities come first – not least when those choices concern AI infrastructure and data.

One striking feature of the defense industry is how openly its major contractors describe and conduct themselves as national assets. Their strategy documents and public messaging rarely present them as neutral global firms that simply happen to have contracts in a given country; instead, they emphasize their contribution to national security, technological sovereignty, and domestic employment, and frame their capabilities as contributing to the country’s long-term resilience. That positioning is not just rhetoric: it shapes where they place facilities, which partnerships they build, and how they respond when national priorities shift.

Over time, the stance is reinforced by how they operate on the ground – investing in local supply bases, co-funding research with universities, building long-term training pipelines, and adapting products to local doctrines and regulatory preferences. This web of relationships makes them hard to dislodge and gives governments a stake in their success. For multinationals in other strategically sensitive sectors, there is a clear lesson: in some markets, it will be more realistic – and ultimately safer – to behave as deeply embedded contributors to a shared national project than as detached global operators who simply happen to do business in a country.

AI has already become an arena in which this kind of positioning matters. Reliance on global providers for GPUs, datasets, and cloud services once seemed innocuous; now, national security reviews scrutinize these dependencies as potential vulnerabilities. A technology firm might build products on internationally developed models yet face pressure to localize training in “friendly” jurisdictions, keep certain categories of data onshore, or integrate with state-approved frameworks for “trustworthy AI”.

In response, defense and security agencies in many countries are working with industry and universities to develop more sovereign AI capabilities – from language models tuned to local legal and cultural norms to analytic systems certified for compliance with national regulatory regimes. For commercial businesses, the implication is similar: AI strategies will need to signal clear “ecosystem allegiance,” using local partners not just for market access but to demonstrate compliance, resilience, and alignment with national expectations about how sensitive technologies are governed.

Defense contracting also shows that firms do not have to make a binary choice between being globally capable and locally acceptable if they are thoughtful about their partnerships. Many global technology providers draw heavily on technology and talent from around the world, yet still play key roles in national defense ecosystems because government-focused contractors sit between them and the state, acting as a translation layer that handles adaptation, compliance, and the day-to-day relationship with government agencies. For multinationals under pressure to demonstrate loyalty to particular jurisdictions, a similar pattern can be attractive. By using specialist partners to localize offerings, align with regulatory and security expectations, and connect to national value chains – including for AI and data-intensive services – they can remain plugged into global innovation while behaving, where it matters, as long-term participants in the national project rather than footloose visitors.