A survey of more than 500 global leaders on quantum AI adoption reveals shifting priorities in 2026, with organizations moving beyond cost concerns toward uncertainty around practical applications. Data and AI firm SAS released the findings at its annual Innovate conference, highlighting how barriers to quantum AI adoption have evolved since its 2025 survey.
The 2026 survey identified six primary barriers to quantum AI adoption. Uncertainty around practical, real-world uses now ranks first among concerns, followed by high cost of implementation. Lack of trained personnel, insufficient knowledge, limited availability of solutions, and unclear regulatory guidelines round out the list.
What Changed From 2025 to 2026
In 2025, high cost of implementation topped the barrier list. The shift toward “uncertainty around practical applications” reflects a maturation in organizational thinking. Companies no longer dismiss quantum AI as purely theoretical. Instead, they seek concrete use cases that deliver measurable returns.
“Organizations of all sizes are eager to develop intellectual property, their original patented approach to quantum AI, so they will be ready as the technology comes of age,” said Bill Wisotsky, Principal Quantum Architect at SAS. “Despite continued strong interest, leaders are proceeding with caution, and they do not want to go all-in on expensive quantum investments they fear may not result in worthwhile use cases and solved problems.”
Understanding Quantum AI
Quantum AI involves running machine learning algorithms on existing quantum hardware. Unlike waiting for purely quantum systems, this hybrid approach allows organizations to accomplish tasks in minutes that traditionally require hours. It can also solve problems once considered impossible on classical systems.
SAS positions classical and quantum computing as opposite ends of a spectrum. Many real-world business problems fall somewhere in the middle, making a hybrid approach practical. Quantum processing and classical processing each handle what they do best, splitting computational workloads efficiently.
SAS Quantum Lab: Bridging the Gap
To address adoption barriers, SAS announced SAS Quantum Lab, launching in Q4 2026 for SAS Viya customers. The offering functions as a hands-on environment for exploring and validating quantum AI ideas without requiring deep quantum physics expertise.
Current testing shows SAS Quantum Lab delivers more than 100 times speedup and 99 percent cost savings compared to traditional approaches. The platform includes side-by-side comparison of classical, quantum, and hybrid results for industry use cases, a virtual quantum AI tutor, and performance-boosting capabilities.
“Leaders are excited to use quantum, but the barriers to entry have been too high, and that requires a solution,” said Amy Stout, Head of Quantum Product Strategy at SAS. “SAS Quantum Lab is designed to be a hands-on playground to learn and innovate for real-world returns on investment.”
Real-World Applications on the Horizon
Survey respondents identified concrete use cases they hope to pursue. These include enhancing fraud detection accuracy in financial services, optimizing 5G network traffic in real-time, accelerating molecular simulation for drug discovery, and improving supply chain logistics. Additional priorities include advancing machine learning for customer behavior prediction and training large language models for natural language processing with reduced optimization time.
Wisotsky concluded: “If you are ready to explore quantum AI, we are ready to work with you. Bring your ideas, and our experts will help determine if and how quantum AI can be incorporated in ways that are valuable, safe and sensible.”
The announcement coincides with SAS Innovate, the company’s global data and AI conference, held as SAS marks 50 years of innovation. Partners supporting the 2026 event include Microsoft, Intel, and AWS.
