The global AI market in 2026: who controls the capability to build?

The picture in the 2026 AI Index

The global AI market combines wider access with a concentration of resources. Stanford HAI’s 2026 AI Index reports that industry produced more than 90% of the notable frontier models in 2025. It records US$285.9 billion in private AI investment in the United States and US$12.4 billion in China that year. Source: Stanford HAI [1].

The report notes that private investment does not fully capture Chinese financing, which also includes government instruments. These numbers should be read with that limitation. Source: Stanford HAI [1].

For an organization building with AI, the next question is operational: what can be developed internally, and which dependencies must be understood before they become difficult to replace?

Our reading: access should become choice

An API can get a project started quickly. Choice lasts longer when the team understands system behavior, controls its knowledge and maintains its own evaluations. These make it possible to test whether changing providers preserves the expected outcome.

For Polybee, technological sovereignty includes the capacity to choose and execute alternatives. Working with global providers and developing in-house expertise can be parts of the same strategy. What matters is clarity about dependencies and the cost of changing them.

This position is stated in our manifesto. It is our lens for interpreting the market, not a conclusion attributed to Stanford.

Four decisions to make during design

1. Behavioral portability

Changing an endpoint is only part of migration. Instructions, response formats, tool calls and error handling also have to work. An application-level evaluation suite helps the team check what changed against criteria it can explain.

2. Control of knowledge

Map where documents, indexes, rules and execution logs live. Keep organizational knowledge separate from the conveniences of one integration. The team should be able to trace information to its source and reconstruct how it entered an answer.

3. Cost per completed task

Token price is only part of the bill. Include retries, human review, failure recovery, latency and infrastructure. An apparently cheaper model may take more work to deliver an accepted result. Measure this in the actual application rather than assuming a winner.

4. Exit conditions

Define how to export data and settings, replace dependencies and test an alternative. A limited migration rehearsal can reveal constraints that an initial demo does not. Documenting those constraints makes the decision clearer.

Building capability is cumulative work

Open models, commercial APIs and local or hybrid execution offer different combinations of control, effort and resources. None removes the need for engineering. The right choice depends on the task, the team and operating conditions.

Polybee’s open-core approach can connect technical openness with sustainable commercial work. A concrete proposal must be examined for what is open, applicable rights of use and reliance on specific services.

The relevant signal is what remains after integration: organized knowledge, evaluation criteria, operational experience and verifiable alternatives. This infrastructure makes it easier to adapt as the market changes.