When a Regional Crisis Becomes a Global Systems Shock
COVID-19 showed how fragile global interdependence becomes when too much capacity is concentrated in too few places. Supply chains cracked, logistics stalled, and what looked efficient suddenly looked dangerously exposed. That should have changed how the world thinks about resilience.
Heidi Tworek’s work on crisis communications helps explain why such shocks do not stay local. Her core point is that crises become systemic not only because of the original disruption itself, but because the infrastructures that carry information, coordination, and public response also carry panic, delay, and cascading failure across borders. COVID-19 revealed this through the overconcentration of manufacturing in China. The current Gulf crisis shows how the next phase of disruption may be even more complex.
Since the escalation around Iran at the end of February, the Gulf has shown how quickly a regional conflict can become a wider systems crisis. Reuters reported on 3 March that more than 21,300 flights had already been cancelled across seven major airports, including Dubai, Doha, and Abu Dhabi. The Strait of Hormuz, through which roughly one-fifth of the world’s crude oil and liquefied natural gas normally moves, became a chokepoint of strategic paralysis. Reuters also reported that drone strikes damaged Amazon Web Services data centers in the United Arab Emirates and Bahrain, disrupting cloud services and showing how quickly kinetic conflict can spill into digital infrastructure.
What begins as a military escalation quickly becomes a systems problem for countries far beyond the battlefield, especially those that remain deeply dependent on external logistics, imported energy, and foreign-controlled digital infrastructure. This is where many governments in the Global South still underestimate the problem.
Artificial intelligence (AI) is often treated as a commercial software layer rather than as strategic infrastructure. That assumption is becoming dangerous. What still looks like a debate about digital innovation is becoming a struggle over resilience, leverage, and continuity under stress.
AI, cloud architecture, and Digital Public Infrastructure (DPI) now function much like highways, ports, and electricity grids once did. They shape how states govern, how markets coordinate, and how societies absorb disruption. If these cognitive and data infrastructures are overwhelmingly controlled from abroad, sovereignty becomes far more fragile than official rhetoric admits.
For the Global South, DPI is where sovereignty becomes operational. Many developing countries cannot rely on a purely market-led path without creating new dependencies, but nor can they simply replicate China’s command-style model. Most still need foreign investment, global technology, and open markets for growth. DPI provides a middle layer of governance, anchoring core rails such as identity, payments, and trusted data exchange while remaining open to global innovation and capital. Without resilient DPI, Sovereign AI remains an ambition without a delivery system.
India offers the clearest large-scale example of this logic in practice. Through India Stack, it has built digital rails for identity, payments, and data sharing at population scale. Aadhaar, Unified Payments Interface (UPI), and the Account Aggregator framework show how a country can remain open to global technology while keeping its core governance rails anchored at home. India’s example matters because it shows that openness and sovereignty can be balanced.
Why the Global South Needs a Digital Risk Lens
Critical digital infrastructure should no longer be treated as politically neutral. In moments of geopolitical escalation, cloud access, model availability, semiconductor supply, cross-border data flows, and cyber resilience can all become instruments of pressure. Linear forecasting is no longer sufficient in a world where physical and digital crises can merge so quickly, amplify one another, and spill across sectors. Policymakers in the Global South need a more adaptive method to map cascading risks: what happens when energy disruption affects compute capacity, when cyberattacks hit regional data centers, or when platform dependency turns a foreign policy crisis into domestic institutional paralysis?
This is where Creative Permutation Foresight (CPF) becomes useful. In practical terms, CPF is a foresight method for exploring how multiple disruptions can combine and reshape policy choices across sectors, rather than being treated as isolated risks. A cyber incident, an export restriction, a maritime blockade, and an AI service interruption may look separate on paper. In reality, they can converge into one systemic crisis.
That recognition should lead to a more deliberate strategy of digital diversification. The answer is not autarky, but strategic hedging. Governments should reduce reliance on a single cloud vendor, a single model ecosystem, or a single infrastructure partner, while distributing compute, data, cybersecurity tools, and identity architecture across multiple technological relationships to improve resilience. Behind that risk lies a broader geopolitical reality: the global digital order is increasingly shaped by competing technology blocs, each seeking to lock countries into its own standards, platforms, and dependencies. From that perspective, the idea of a Digital Non-Aligned Movement (NAM) is urgent, not as a nostalgic echo of Cold War rhetoric, but as a pragmatic framework for the AI era—one that allows the Global South to benefit from global innovation without becoming structurally hostage to one technological bloc.
The False Promise of Digital Autarky
Some discussions on digital sovereignty still drift too easily into fantasies of total self-sufficiency, as if emerging economies could or should immediately build their own full semiconductor chains, advanced GPU capacity, and entirely domestic AI stacks. For most countries, that is economically unrealistic and strategically distracting. The more credible path is not autarky, but strategic interdependence.
Strategic interdependence means accepting that deep connectivity will remain part of the global economy while ensuring that this connectivity does not become a single point of failure. For the Global South, that means focusing less on symbolic self-reliance and more on graceful degradation. If an external disruption hits, critical systems should not collapse all at once. Payment systems, public services, digital identity functions, and core decision architectures should be able to continue operating, even in reduced form.
This is where control over the logic layer becomes decisive. Most countries may still depend on imported hardware, foreign chips, or global manufacturing ecosystems for years to come. But dependency at the hardware level does not need to translate into surrender at the governance level. If governments retain control over strategic data, public digital rails, AI decision parameters, and national regulatory standards, then imported infrastructure remains a tool: important, but not sovereign in itself.
A Third Way for the AI Era
If short-term diversification is about survival, long-term strategy must be about shaping power. The Global South needs a digital third way: neither passive dependence on foreign technological architectures nor isolationist fantasies of withdrawal.
This is where the Algorithm of Aspire (AoA) becomes useful. Put simply, AoA is an approach to building AI and institutional strategy around a society’s own developmental priorities, ethical thresholds, and institutional realities, rather than importing the assumptions embedded in foreign platforms. Sovereign AI, in that sense, is not a branding exercise or a prestige project. It is the capacity to shape the cognitive architecture of national systems: how models are trained, what assumptions they encode, what forms of knowledge they prioritize, and whose realities they misread.
Two foundations matter here. The first is cognitive sovereignty, because imported models can also import distortions, false alarms, and institutional assumptions that do not fit local realities. The second is energy resilience. AI runs on compute, and compute runs on energy, which means digital sovereignty will depend not only on data governance or model regulation, but also on whether countries can keep critical computing infrastructure running during embargoes, price shocks, or geopolitical disruption.
The next crisis will not arrive politely. It may travel through fiber-optic cables as fast as it moves through shipping lanes, and countries that fail to prepare will discover too late that digital dependency is not efficiency by another name but vulnerability by another route. That is why Digital NAM matters externally, while Sovereign AI provides the domestic cognitive and infrastructural capacity to make that posture credible.
None of this will be easy. Governments need technological literacy and long-term strategic patience to invest in infrastructure whose payoff may not align with populist politics, especially under fiscal constraints. Any serious push for Sovereign AI and stronger DPI will also face pressure from markets and from narratives that portray domestic digital rails as anti-innovation. Beyond that lies a deeper diplomatic problem: the trust deficit within the Global South itself. Without stronger strategic trust, common standards, and bargaining discipline, even the most compelling vision of Digital NAM risks remaining a slogan rather than a negotiating force.
The real question is whether the Global South will remain a user of systems shaped elsewhere, or begin building the strategic capacity to negotiate the next crisis on its own terms.
