AI workloads won’t run at scale on quantum hardware soonNo enterprise AI workload at scale will run on quantum hardware by 2028 and classical accelerated AI will dominate every production benchmark according to Gartner. “Quantum AI” refers to AI or machine learning (ML) techniques that require execution on quantum hardware to achieve a claimed performance, cost or capability advantage over classical computing. Quantum AI is different from three commonly conflated categories:Classical AI : AI models, such as deep learning, transformers and reinforcement learning, that run entirely on CPUs, GPUs or TPUs and deliver measurable enterprise ROI today. These techniques already deliver value in optimisation, simulation and sampling workloads and do not depend on quantum hardware. When vendors claim to deliver “quantum AI,” they usually refer to hybrid or quantum-inspired techniques, not quantum-native AI running at enterprise scale.