What changed in the AI-assistant market?
For the first time, no single assistant holds a majority. ChatGPT reportedly slipped below 50 percent share while Gemini rose toward 28 percent and Claude toward 10 percent. The era of one obvious default is over. The leaders now leapfrog each other on capability and price, and the best choice for one task is rarely the best for the next.
Why is betting on one model now a risk?
Because a single model means inheriting all of its weaknesses at once. Its pricing, its outages, its policy changes, and its blind spots become yours, with no alternative ready when any of them moves against you. When the field was a near-monopoly, standardizing on the leader was defensible. Now it quietly locks you to whoever happens to lead today, in a race where the lead changes constantly.
What does a multi-model strategy look like?
It routes each task to the model that does it best or most cheaply, behind a layer that lets you switch providers without rewriting your work. It compares cost and quality continuously rather than once. It governs access and data centrally, so using several models does not mean several blind spots. Done well, it turns the fragmenting market from a problem into leverage: you use the best of each, and you are captive to none.
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