Quantifying Systemic Vulnerability in the Foundation Model Industry

TL;DR

This paper introduces the AIIVI, a new index to measure systemic vulnerability in the foundation model industry, highlighting energy infrastructure as a critical constraint and demonstrating a novel methodology for assessing opaque, rapidly evolving sectors.

Contribution

The paper develops the AIIVI index based on O-Ring theory and implements a human-in-the-loop approach using language models to extract indicators from grey literature.

Findings

AIIVI score of 0.82 indicates high vulnerability

Energy infrastructure is a key emerging constraint

Methodology applicable to other opaque industries

Abstract

The foundation model industry exhibits unprecedented concentration in critical inputs: semiconductors, energy infrastructure, elite talent, capital, and training data. Despite extensive sectoral analyses, no comprehensive framework exists for assessing overall industrial vulnerability. We develop the Artificial Intelligence Industrial Vulnerability Index (AIIVI) grounded in O-Ring production theory, recognizing that foundation model production requires simultaneous availability of non-substitutable inputs. Given extreme data opacity and rapid technological evolution, we implement a validated human-in-the-loop methodology using large language models to systematically extract indicators from dispersed grey literature, with complete human verification of all outputs. Applied to six state-of-the-art foundation model developers, AIIVI equals 0.82, indicating extreme vulnerability driven by compute infrastructure (0.85) and energy systems (0.90). While industrial policy currently emphasizes semiconductor capacity, energy infrastructure represents the emerging binding constraint. This methodology proves applicable to other fast-evolving, opaque industries where traditional data sources are inadequate.