Gartner Predicts Enterprise AI Workloads Will Not Run on Quantum Hardware Through 2028

Brickinfo News Agency – Enterprise AI workloads at scale will not run on quantum hardware through 2028, with classical accelerated computing continuing to dominate all production benchmarks, according to the latest market insights from Gartner, Inc.

The research firm reports that no peer-reviewed results have demonstrated a quantum advantage on any production AI application to date. Chirag Dekate, VP Analyst at Gartner, noted that vendor claims regarding quantum AI typically refer to hybrid or quantum-inspired algorithms running on conventional hardware rather than true, quantum-native execution at an enterprise scale. Fault-tolerant quantum computing is not expected to handle production AI workloads for the remainder of the decade due to current limitations across hardware, error correction, middleware, and algorithms.

Gartner distinguishes true quantum AI, which requires quantum hardware to achieve performance advantages, from existing classical AI, quantum-inspired classical models, and experimental hybrid workflows. Because fault-tolerant quantum computing will remain in research and development with insufficient logical qubits through 2030, enterprise boards are cautioned against diverting active AI deployment budgets into experimental quantum R&D that cannot yield near-term returns.

To maintain operational efficiency, the firm advises organizations to separate quantum R&D from production AI budgets, noting that generative AI demonstrates measurable returns within 12 to 18 months, whereas quantum computing has not yet shown tangible returns on production workloads. Enterprises are advised to leverage quantum-inspired algorithms on existing GPU infrastructure, set strict termination criteria for pilot projects, and track meaningful metrics such as logical qubit stability and error rates rather than total physical qubit counts.