AI systems fail gradually and partially, not in clear binary states like traditional software. IBM research shows only 48% of AI models reach production. The model gives a plausible answer missing important context, latency spikes but stays under timeout limits, outputs degrade invisibly. Your AI error handling must match this reality.
When ChatGPT went down for 12 hours in June 2025, thousands of businesses had no fallback. IDC predicts 70 percent of top AI enterprises will use multi-model routing by 2028. Task-specific routing can cut inference costs by up to 85 percent. Resilience through model diversity is not optional.
The most damaging AI incidents stem from process breakdowns, not technical failures. The AI Incident Database reached 1000 incidents by 2025, with GenAI involved in 70% of cases. Building incident response that addresses process causes rather than just technical symptoms is what prevents repeat failure.