Quantum as the Infrastructure Behind AI's Next Leap
By Nadine Kugler, QAI Ventures
At the ITU AI for Good Summit in Geneva, practitioners from IBM, the World Economic Forum, national governments, and leading research institutions converged on a question that is moving from academic to operational: at which points in the AI value chain does quantum technology create a material advantage over classical approaches?
Quantum and AI are distinct technologies with different underlying principles. What is becoming clearer, however, is that quantum capabilities, in sensing, cryptography, and simulation, address specific structural limitations of classical AI systems. The following four areas stood out as most relevant for industry leaders evaluating their technology roadmaps.
1. Quantum Is Already Accelerating AI Development
AI is not waiting for a fault-tolerant quantum computer to arrive. Companies like SandboxAQ Sandbox AQ uses AI and quantum(-inspired) methods to build new models that can improve developments in quantum chemistry, molecular modelling etc., large quantitative models, that outperform classical approaches in drug discovery and materials science. These models run on today's GPUs, informed by quantum principles. The feedback loop between quantum and AI is active now.
2. Your AI Networks Are Only as Strong as Your Cryptography
Every AI system generates, transmits, and stores data. That data is at risk. The US government's Executive Order 14412 mandated migration to post-quantum cryptography for all high-value federal systems by 2030–2031 — the fastest major cryptographic transition in history. For industry leaders: if your AI infrastructure relies on current asymmetric encryption, your transition window is already narrowing. The time to act is now, not when a quantum computer makes the threat visible.
3. Quantum Sensing Is Feeding AI With Data It Could Never Access Before
AI models are only as good as their data. Quantum sensors are generating entirely new categories of data, brain activity measurements, molecular-level environmental signals, precision navigation independent of GPS, that classical sensors cannot produce. The organisations deploying AI on top of quantum sensing data will operate with an informational advantage that compounds over time.
4. The Ecosystem Is the Competitive Moat
At AI for Good, the consistent message from IBM, the World Economic Forum, and national governments was the same: the bottleneck is not technology — it is coordination. The organisations building cross-sector relationships now, connecting their AI roadmaps to quantum hardware developers, research institutions, and standards bodies, are building a structural advantage that capital alone cannot replicate later.
The practical implication: quantum is not a future consideration for your AI strategy. It is the infrastructure layer your AI strategy is missing.
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