AI Is Not a Commodity When It Sits at the Heart of the Business
Anyone can rent the same model. The advantage is the context around it: the workflows, the judgment, the evidence and the people who know what to do when it is wrong.
The model is becoming a utility. The price falls, the capability rises, and every competitor can buy the same endpoint. That is what a commodity looks like. The mistake is to conclude that AI itself is therefore not a source of advantage. The advantage was never in the model.
What you can buy
You can buy access, prompts, a generic course, a copilot and a licence. You can buy all of it this quarter. Your competitor can buy the same list, often for less, and the gap between you closes before the pilot ends.
What you cannot buy
You cannot buy your own context: the customers, the constraints, the history and the exceptions that make your business work. You cannot buy the workflow redesign that turns a demo into a different Monday. You cannot buy the judgment of the person who knows when the output is wrong, or the evidence that lets a regulator see how the decision was made.
Why this matters for adoption
This is why tool-led adoption stalls. The licence is bought, the training is attended, and the work does not change. The missing layer is the one that connects the model to the way the company actually decides, serves and operates. That layer is designed, not purchased.
The test
Ask three questions about any AI initiative. Whose context does it encode? Which workflow changes because of it? Who is accountable when it is wrong? If the answers are thin, the initiative is a commodity purchase with a transformation label. If the answers are specific, it is becoming part of the business.
Conclusion
AI knowledge is not a commodity when it is embedded in the business. The model can be rented. The context, the capability and the accountability cannot. That is where the work is, and it is why we start with the business problem, not the tool.