MIT AI Risk Repository · Risk Sub-Category · 45.01.13

Risks from AI systems (Risks of supply chain security)

Category: AI's inherent safety risks

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Description

"The AI industry relies on a highly globalized supply chain. However, certain countries may use unilateral coercive measures, such as technology barriers and export restrictions, to create development obstacles and maliciously disrupt the global AI supply chain. This can lead to significant risks of supply disruptions for chips, software, and tools."

From AI Safety Governance Framework (TC2602024), as extracted by the MIT AI Risk Repository (CC BY 4.0).

Classification

Domain: 6. Socioeconomic & Environmental
Subdomain: 6.4 Competitive dynamics
Causal entity: Human
Intent: Intentional
Timing: Pre-deployment

Subdomain definition: AI developers or state-like actors competing in an AI ‘race’ by rapidly developing, deploying, and applying AI systems to maximize strategic or economic advantage, increasing the risk they release unsafe and error-prone systems.

Real-world incidents in this subdomain

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How other frameworks describe this risk

Increased competition
A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)
Geopolitical risk
Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)
Worsened conflict
A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values (Clarke2023)
Resource conflicts driven by AI development
A Survey of the Potential Long-term Impacts of AI: How AI Could Lead to Long-term Changes in Science, Cooperation, Power, Epistemics and Values (Clarke2023)
Type 4: Willful indifference
TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)
Competitive pressures in GPAI product release
Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)
Opacity (industry opacity)
Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)
Corporate AI Race
An Overview of Catastrophic AI Risks (Hendrycks2023)

Other entries from TC2602024

AI's inherent safety risks Risk Category
Risks from models and algorithms (Risks of explainability) Risk Sub-Category · 7.4
Risks from models and algorithms (Risks of bias and discrimination) Risk Sub-Category · 1.1
Risks from models and algorithms (Risks of robustness) Risk Sub-Category · 7.3
Risks from models and algorithms (Risks of stealing and tampering) Risk Sub-Category · 2.2
Risks from models and algorithms (Risks of unreliable output) Risk Sub-Category · 3.1
Risks from models and algorithms (Risks of adversarial attack) Risk Sub-Category · 2.2
Risks from data (Risks of illegal collection and use of data) Risk Sub-Category · 2.1
Risks from data (Risks of improper content and poisoning in training data) Risk Sub-Category · 1.2
Risks from data (Risks of unregulated training data annotation) Risk Sub-Category · 7.3
Risks from data (Risks of data leakage) Risk Sub-Category · 2.1
Risks from AI systems (Risks of exploitation through defects and backdoors) Risk Sub-Category · 2.2