Forbes May 30, 2025
As AI adoption accelerates, the AI model supply chain is becoming a critical but often underexamined source of risk. From third-party training data to prebuilt models and infrastructure dependencies, there are layers of exposure that aren’t always visible until something breaks. If you’re deploying or integrating AI at scale, these blind spots can quietly introduce bias, security vulnerabilities or compliance gaps.
The challenge is knowing where to look and how to respond without slowing innovation. Below, Forbes Technology Council members share what to keep on your radar and how to build more resilience into your AI pipeline.
1. Reduce Cloud Dependence
One overlooked risk is cloud dependence. The “large” in the popular large language models usually needs giant data centers...
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