Why Enterprise AI Fails: Fragmented Data, Not Model Choice

Your AI copilot demo worked. The model answered every question in the sandbox, latency was fine, and the stakeholders nodded. Then you connected it to production and the answers turned vague, wrong, or quietly incomplete. The reflex is to blame the model — swap one vendor for another, try a fine-tune, wait for the next release. That rarely fixes anything, because the model was probably never the problem. Enterprise AI rollouts stall on data, not intelligence. Customer information is spread acro...