Gartner says enterprise AI workloads will not run on quantum hardware before 2028

Gartner has predicted that no enterprise AI workload at scale will run on quantum hardware through 2028, with classical accelerated AI expected to remain the dominant platform for production AI workloads.

The research firm said there is currently no peer-reviewed evidence demonstrating a quantum advantage for production AI workloads, adding that most vendor claims around “quantum AI” refer to hybrid or quantum-inspired techniques rather than quantum-native AI.

According to Gartner, fault-tolerant quantum computing will remain in the research phase for AI through 2030 due to limitations in hardware, error correction, middleware and algorithms. It advised enterprises to keep quantum research budgets separate from AI production investments, given their differing timelines and expected returns.

Gartner also recommended that organisations prioritise quantum-inspired algorithms running on existing GPU infrastructure, establish clear success criteria for quantum pilots, and focus on progress in logical qubits and error correction rather than physical qubit counts.

“When vendors claim to deliver ‘quantum AI,’ they usually refer to hybrid or quantum-inspired techniques, not quantum-native AI running at enterprise scale,” said Chirag Dekate, Vice President Analyst at Gartner.

“Quantum AI has never returned measurable value on any production workload, and is unlikely to do so for the foreseeable future,” Dekate added.