Infrastructure Dependency

Definition

Infrastructure dependency describes the condition in which essential services — including energy grids, financial systems, healthcare networks, transportation, and communications — rely on shared AI components to function. This reliance creates systemic vulnerability: when multiple critical systems depend on the same foundation models, cloud-hosted AI services, or shared data pipelines, a single point of failure can propagate disruptions across otherwise unrelated sectors. Infrastructure dependency differs from ordinary software dependency in that AI systems can fail in unpredictable ways, including gradual performance degradation, confident hallucination, and emergent behavioural changes following model updates that do not trigger conventional error-handling mechanisms.

How It Relates to AI Threats

Infrastructure dependency is a core concern within the Systemic and Catastrophic Threats domain. Under the infrastructure dependency collapse sub-category, this threat pattern addresses scenarios where the concentration of critical services on a small number of AI providers or foundation models creates fragility at a societal scale. A disruption to a widely used AI service — whether through technical failure, cyberattack, or business discontinuity — could simultaneously affect healthcare diagnostics, financial trading, energy management, and emergency response systems. The opacity of AI supply chains means that organizations may not fully understand their own dependency on specific AI components shared across their infrastructure.

Why It Occurs

• Market concentration drives critical sectors to adopt AI services from a small number of dominant providers
• Cost efficiency incentives encourage shared infrastructure over redundant, independent AI deployments
• AI supply chains are opaque, making it difficult for organizations to map their full dependency on specific models or services
• Procurement decisions prioritize capability and cost over resilience planning and vendor diversification
• Regulatory frameworks have not yet established requirements for AI infrastructure diversity or mandatory fallback systems

Real-World Context

While no specific incidents in the TopAIThreats taxonomy currently document AI infrastructure collapse, historical analogues — including the 2021 Fastly CDN outage that disabled major websites globally and the 2024 CrowdStrike update failure that grounded flights and disrupted hospitals — illustrate how shared digital infrastructure creates systemic vulnerability. As AI is embedded into critical systems, the concentration of foundation model providers and cloud AI services reproduces these risks at a potentially larger scale. The EU AI Act’s provisions on systemic risk from general-purpose AI models and ongoing discussions at the OECD on AI resilience reflect growing regulatory attention to this threat pattern.