AI's Hidden Concentration Risk Looks Nothing Like Before
Source: Featured Blogs - Forrester
The shift from monolithic infrastructure to distributed AI models has created new concentration points that existing risk frameworks miss—not at the supplier level, but in the training data, model weights, and inference infrastructure that dozens of companies now depend on identically. Organizations optimizing for speed are replicating the same foundation models, fine-tuning approaches, and cloud compute stacks. A vulnerability in OpenAI's infrastructure or a corrupted training dataset affects the entire ecosystem simultaneously rather than isolating to one vendor. This inverts decades of enterprise risk mitigation: buying more vendors increases systemic fragility when they're all running the same underlying technology.