Everyone is obsessed with which AI model to use. It is the wrong question.
The model became a commodity. The competitive moat moved, and it now sits in the living data of your own operation, which nobody can buy ready-made.
For the past few years the race has been about raw power. Which model is smarter, which one has more parameters, which one passed which benchmark. And because everyone has more or less the same access to frontier models, that advantage evaporates the day after a competitor ships.
The model became a commodity. The difference no longer lives inside it.
The real advantage sits in what the model never had: your data. A generic AI model knows the entire internet and absolutely nothing about your operation. It knows the world, it does not know your company. And what it does not know is exactly what decides who wins.
When you connect AI to the living data of your business, to the ERP, the CRM, finance, supply, it stops giving clever generic answers and starts giving decisions anchored in your reality. Two companies can run exactly the same model and get opposite results, because what feeds the AI is different.
This is why I say the competitive moat moved. It is not the model, it is the data. And good data is not bought ready-made, it is built over years of operation, integration and discipline.
What worries me is watching companies spend fortunes choosing the perfect model while their data stays trapped in silos, dirty and disconnected. It is buying the most powerful engine in the world and forgetting there is no fuel.
The question I leave you with: is your company competing for the best AI model, or building the data that would make any model work in its favor?