Quantum computing is poised to follow generative AI as the next disruptive force in data analytics. In an April 2025 pulse survey of 500 business managers in China, France, Mexico, the UK, and the US, 71 % said they’re familiar with Quantum AI, and 60 % report active projects or budget allocation.
What’s Holding Companies Back?
Respondents highlighted:
| Obstacle | Share of Leaders |
|---|---|
| Up-front cost | 38 % |
| Skills / knowledge gap | 35 % |
| Unclear business value | 31 % |
| Talent shortage | 31 % |
| Regulatory uncertainty | 26 % |
How SAS Closes the Gap
- Hybrid optimisation pilots: Proof-of-concept projects that blend quantum annealing with SAS’ classical solvers to tackle large-scale optimisation.
- SAS Viya Workbench: A self-service, on-demand environment where data scientists can spin up quantum solvers without mastering quantum physics.
- Ecosystem alliances: Membership in IBM Quantum Network and QuEra Quantum Alliance, plus collaboration with D-Wave, gives customers access to multiple hardware modalities.
“Our goal is to deliver quantum ready answers without forcing customers to become quantum physicists,” says Bill Wisotsky, Principal Quantum Architect, SAS
Early Use-Cases Taking Shape
- Drug discovery: accelerate molecule screening.
- Risk modelling: crunch ultra-complex financial scenarios.
- Smart manufacturing: optimise materials and production lines.
- Cyber-defence: strengthen encryption and threat detection.
- Logistics: fine-tune multi-variable routing in real time.
SAS plans to embed quantum connectors directly into Viya so developers can experiment with quantum algorithms alongside familiar Python, R, or SAS code, speeding the journey from “quantum curiosity” to measurable ROI.
Interest in quantum AI is surging, but many organisations still need a clear, trusted path to adoption. With its hybrid architecture, enterprise-grade platform, and network of hardware partners, SAS is positioning itself as that bridge.
