As the supply chain to support quantum hardware stabilises, many experts anticipate that this emerging technology will be popularised and production-ready by the early 2030s. Some assume that means benefitting from quantum now is out of the question. 

Enter quantum AI, a powerful approach involving running machine learning algorithms on existing quantum hardware. In practice, applying quantum AI can look like helping organisations accomplish hours-long tasks in minutes, or rendering problems once considered impossible to realise on existing hardware. It can also look like calibrating models to learn efficiently on less data, bolstering stability over time – and much more. 

So, with all its potential benefits, what’s holding back organisations from greater investment? 

Data and AI leader SAS surveyed more than 500 global leaders across industries on quantum AI. In the first instalment of the survey in 2025, high cost of implementation ranked as the number one barrier to adoption, followed by lack of understanding or knowledge. That’s changed in 2026. 

What are the top barriers to quantum AI adoption in 2026? 

The greatest barriers to quantum AI adoption in 2026 ranked as follows among survey respondents:

    Uncertainty around practical, real-world uses
    High cost of implementation
    Lack of trained personnel
    Lack of knowledge or understanding
    Limited availability of quantum AI solutions
    Lack of clear regulatory guidelines 

What is quantum AI, and why do organisations want to use it? 

SAS looks at classical and quantum computing as a spectrum: with proven classical computing on one end, and experimental and exponentially more powerful quantum computing on the other. Many industry and business problems fall somewhere in the middle, with a hybrid approach splitting workloads: quantum processing and classical processing each doing what they do 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,” said 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 and solved problems. SAS is working to level the playing field, establishing real-world use cases for today, and ensuring that customers can get a piece of the quantum pie tomorrow.”
 
How can customers prepare for the quantum economy? 

“This survey illuminates what SAS experts were already seeing in the market: that 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 is excited to give a sneak peek of SAS Quantum Lab, a hands-on playground to learn and innovate for real-world ROI.” 

What is SAS Quantum Lab? 

Coming in Q4 to SAS Viya customers, SAS Quantum Lab is a launchpad for the quantum AI journey. It’s designed to be a complement to quantum experts on their existing work, and to empower users who may not be quantum physicists, but are ready to explore, test and validate their ideas. It significantly reduces the cost of quantum AI exploration and helps customers avoid false signals, all while exploring this powerful technology efficiently and credibly. 

SAS Quantum Lab is currently being designed to include the following:

    The ability to compare, side-by-side, classical, quantum and hybrid results for industry use cases, letting users find the best solutions for their business problems.
    Performance-boosting capabilities, with current testing showing more than 100 times speedup and 99% cost savings.
    A virtual quantum AI tutor to accelerate learning by answering questions, offering sample code and suggesting next steps. 

What could be possible with quantum AI? 

At the conclusion of the survey, respondents had the option to answer a write-in question; if they were currently working on quantum, what use cases did they hope to achieve, or what business problem would they like to solve? Responses included the following: 

    To enhance the accuracy of fraud detection systems in financial serves, enabling more efficient identification of complex transaction patterns.
    To optimise 5G network path traffic in real-time.
    To accelerate molecular simulation and the drug discovery process for new therapeutic candidates.
    For supply chain distribution and to optimise logistics problems.
    To improve machine learning workflows with a focus on predictive modeling for customer behaviour.
    To train large language models for natural language processing tasks, reducing the time and resources for model optimisation.
 
“If you’re ready to explore quantum AI, we’re ready to work with you,” added 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.” 

Connect with quantum AI at SAS Innovate 

This announcement was made at SAS Innovate, the company’s global data and AI conference, as SAS celebrates 50 years of innovation. This year's event is proudly supported by our partner sponsors, including Microsoft, Intel and AWS. 

About SAS

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