There is a peculiar assumption that clings to quantum computing like a stubborn shadow: that it remains a distant prospect, a technology for the 2030s, something to monitor from a safe distance.
The supply chain for quantum hardware is indeed stabilising, and many experts anticipate production-ready systems by the early 2030s. But to assume that benefiting from quantum now is out of the question is to misunderstand the transformative potential of quantum AI.
Quantum AI involves running machine learning algorithms on existing quantum hardware. In practice, this means accomplishing hours-long tasks in minutes, rendering problems once considered impossible suddenly tractable, and calibrating models to learn efficiently on less data with greater stability over time. It is not a future promise; it is a present capability.
So why aren't more organisations diving in?
The barriers are shifting
A SAS survey of more than 500 global leaders across industries on quantum AI, reveals an interesting evolution in executive thinking.
In 2025, the high cost of implementation ranked as the number one barrier to adoption, followed by a lack of understanding or knowledge. By 2026, the landscape has shifted.
The greatest barrier today is uncertainty around practical, real-world uses. Cost now sits in second place, followed by a lack of trained personnel, lack of knowledge or understanding, limited availability of quantum AI solutions, and finally, a lack of clear regulatory guidelines.
What this tells us is that leaders have moved past the initial hesitation about expense and complexity. They are now asking a more sophisticated question: what can we actually do with this technology?
The hybrid approach
SAS envisions classical and quantum computing as a spectrum. At one end lies proven classical computing—reliable, understood, and capable. At the other lies experimental and exponentially more powerful quantum computing. Many industry and business problems fall somewhere in the middle, with a hybrid approach splitting workloads between quantum and classical processing, each doing what it does best.
"Organisations of all sizes are eager to develop intellectual property—their original, patented approach to quantum AI—so they'll be ready as the technology comes of age," explains Bill Wisotsky, principal quantum architect at SAS. "Despite continued strong interest, leaders are understandably proceeding with caution, and they don't want to go all-in on expensive quantum investments they fear may not result in worthwhile use cases."
Enter SAS quantum lab
This is where SAS Quantum Lab enters the picture. Coming in Q4 to SAS Viya customers, it is designed as a launchpad for the quantum AI journey, a hands-on playground to learn and innovate for real-world ROI. Crucially, it is built to empower users who may not be quantum physicists but are ready to explore, test, and validate their ideas.
The lab significantly reduces the cost of quantum AI exploration and helps customers avoid false signals. Current testing shows more than 100 times speedup and 99% cost savings compared to alternative approaches. Users can compare classical, quantum, and hybrid results side-by-side for industry use cases, finding the best solutions for their business problems. A virtual quantum AI tutor accelerates learning by answering questions, offering sample code, and suggesting next steps.
Real-world applications
When survey respondents were asked to describe their quantum AI aspirations, the responses painted a picture of tangible business transformation.
Financial services leaders want to enhance fraud detection accuracy by identifying complex transaction patterns. Telecommunications experts aim to optimise 5G network path traffic in real-time.
Pharmaceutical researchers seek to accelerate molecular simulation and drug discovery. Supply chain professionals want to solve logistics optimisation problems.
Marketers hope to improve predictive modelling for customer behaviour. And AI practitioners want to train large language models with reduced time and resources.
"If you're ready to explore quantum AI, we're ready to work with you," adds Wisotsky. "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 quantum future is not arriving in the 2030s. It is being built today, one hybrid workload at a time.
