Stop Asking Which AI Model to Use. Start Asking Who Owns the Output
A team I worked with spent three months comparing large language models.
They ran benchmarks, evaluated output quality, negotiated pricing, and finally selected a provider. They connected it to their content workflow and waited for the magic. It felt like the best option.
Within a month, the project was in trouble. Outputs were inconsistent, deadlines slipped, and senior team members started bypassing the system entirely.
The model was fine. The problem was that no one owned the output.
Three different departments touched each piece of content. Each one assumed another had checked brand alignment. No one had explicit authority to approve, block, or revise. The AI generated text quickly. The organization couldn't decide what to do with it.
This is the most expensive mistake I see in enterprise AI implementations. Teams obsess over capability and ignore accountability. They ask which model is best when they should ask who decides what...
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