Why AI breaks without context — and how to fix it

AI performance in enterprises depends less on the model and more on clean, unified context and data architecture.

Fragmented, stale production data leads to generic output, while strong signals produce much better results.

The article says businesses need streaming, identity-resolved context layers to make AI useful in practice.

Better AI starts with real-time data integration, customer identity resolution, and current context across systems.