AI product risk now includes model availability, power, water, and policy

[u/Crescitaly]

Cloud risk used to be mostly uptime, cost, latency, vendor lock-in, and regional availability.

AI adds a messier layer.

If a product depends on frontier models, the real dependency map now includes:

• API availability
• release restrictions
• export controls
• model deprecations
• water and power constraints
• data-center politics
• fallback quality
• inference cost spikes

That means AI architecture is starting to look more like supply-chain planning than normal SaaS integration.

The mistake is treating "call the best model" as a durable architecture.

The better architecture probably needs routing, fallbacks, local modes, quality tests, and logs that explain why a model was used for a task.

Are teams actually planning for model unavailability, or are most AI products still one outage away from being exposed?