The two defining technologies of the decade are starting to accelerate each other. This is the convergence that matters.
Quantum machines open new ways to compute the math that AI depends on. They can sample from rich probability spaces, explore optimization landscapes, and simulate systems that are out of reach today. As the hardware matures, expect new model families and training methods that simply were not possible on classical machines alone.
The relationship runs both ways. AI is already helping researchers design better qubits, tune delicate control systems, and crack the hard problem of error correction. In other words, AI is one of the tools making useful quantum computers arrive sooner. Each field is becoming a force multiplier for the other.