Quantum computing unlikely to power enterprise AI at scale by 2028

Gartner predicts that enterprise-grade AI workloads will not run at scale on quantum hardware by 2028. The advisory firm notes a lack of peer-reviewed evidence demonstrating a quantum advantage for production-level AI, suggesting that classical accelerated AI will continue to dominate production benchmarks throughout the decade.

Chirag Dekate, a VP Analyst at Gartner, stated that true quantum computing is unlikely to be ready for production AI workloads for the remainder of this decade. He noted that current claims of ‘quantum AI’ often refer to hybrid or quantum-inspired techniques rather than native quantum execution. Achieving fault-tolerant quantum computing requires significant advancements in hardware, error correction, middleware, and algorithms.

In the investment landscape, companies like Alphabet and IonQ are pursuing different technological pathways. Alphabet utilizes superconducting computing, prioritizing speed, while IonQ focuses on trapped ion technology, prioritizing accuracy. While industry projections suggest viable quantum technology could arrive around 2029, the timelines for quantum R&D and AI production infrastructure remain largely incompatible.