Many experts predict that quantum technologies will reach production maturity with the stabilisation of the supply chain supporting quantum hardware, and that we will have to wait until early next decade for widespread adoption. For parts of the market, this has so far meant one thing: the real benefits of quantum computing remain a distant prospect.
Against this backdrop, however, comes the concept of quantum AI – the approach of running machine learning algorithms on the quantum infrastructure available today. In practice, this means that computational processes can be shortened from hours to minutes, and problems previously considered unfeasible on classical hardware can be solved. The technology also makes it possible to train models more efficiently with smaller data sets and increase their stability over time.
Quantum AI: a hybrid model as a way forward
SAS views classical and quantum computing as a continuum – from proven classical systems to experimental but exponentially more efficient quantum systems. In practice, more and more business problems are located between these poles, leading to the development of hybrid architectures that share tasks between both types of processing.
As Bill Wisotsky, Principal Quantum Architect at SAS, points out, organisations are actively building their own quantum AI competencies and intellectual property in preparation for the technology’s moment of full maturity.
– Despite continued strong interest, leaders are acting cautiously and do not want to invest significant resources in costly quantum solutions that may not translate into real-world applications and useful solutions, adds Bill Wisotsky.
Preparing for a quantum economy
– Leaders are excited about the possibilities of quantum, but the barriers to entry are too high, said Amy Stout, director of quantum product strategy at SAS. – The new SAS Quantum Lab test environment is intended to be the answer.
What is SAS Quantum Lab?
SAS Quantum Lab, which will be coming to SAS Viya customers in Q4 2026, is a starter platform for the quantum AI journey. It is designed to complement the work of quantum experts, while also aiming to enable users who want to explore, test and validate their ideas.
The platform significantly reduces the cost of experimenting with quantum AI and helps clients avoid erroneous conclusions while enabling efficient and reliable use of the technology.
Currently planned features include:
- The ability to compare classical, quantum and hybrid results for industry applications to find the best solutions to business problems.
- Increased efficiency – tests show more than 100-fold acceleration and 99% cost savings.
- A virtual quantum AI teacher that accelerates learning by answering questions, providing example code and suggesting next steps.
