Why AI teams should compare renting and owning models
On July 1, 2026, Palantir CEO Alex Karp criticized large AI labs for charging companies by the token while giving them too little useful value. The central point is that a rented leaves the company without the , with limited ability to inspect how an answer was produced, and with a risk that its internal data may help improve the vendor's product. Running a model on company-owned keeps the , data, and under the company's control.
Renting can be fine for low-risk work, but regulated work has a much higher need for control. The practical question is whether high token spending is producing real value, and whether a company's data and business edge are leaking into outside .
Key points
- Token-based pricing can become expensive when run many tasks.
- A rented gives the company less control over and answer review.
- Company-owned can keep data and records inside the business.
- Renting may still be fine for low-risk work.
- Regulated work needs stronger control over data, cost, and review records.