SAS Finds Uncertainty Tops Quantum AI Barriers Now

More than 500 global leaders recently identified uncertainty around practical applications as the primary obstacle to adopting quantum AI, surpassing even implementation costs, according to a new survey by SAS. This shift signals a maturing understanding of the technology and a growing demand for demonstrable value as the supply chain for quantum hardware stabilizes with anticipated widespread availability by the early 2030s. “Organizations of all sizes are eager to develop 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. SAS is responding with SAS Quantum Lab, a forthcoming tool designed to lower the barriers to entry and help organizations explore real-world return on investment from this emerging field.

2026 SAS Quantum AI Adoption Survey Findings

SAS surveyed more than 500 global leaders to assess the current state of quantum AI readiness, revealing a critical skills gap is also hindering progress. Beyond cost and knowledge deficits, a lack of clear regulatory guidelines is emerging as a barrier, suggesting organizations are proactively considering the long-term implications and potential compliance challenges of quantum AI. Amy Stout, Head of Quantum Product Strategy at SAS, explains, “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.” Respondents envision applications ranging from enhanced fraud detection in financial services to optimizing 5G network traffic and accelerating drug discovery, demonstrating a broad spectrum of potential use cases if these hurdles can be overcome.

SAS Quantum Lab: Enabling Hybrid Classical-Quantum Workloads

The convergence of classical and quantum computing is no longer a distant prospect; organizations are actively seeking pathways to integrate these technologies, even as practical implementation hurdles remain significant. While early anticipation focused on the cost of quantum hardware, a recent SAS survey of over 500 global leaders reveals a shift in primary concerns. Uncertainty surrounding demonstrable, real-world applications has now surpassed cost as the biggest impediment to quantum AI adoption, indicating a maturing expectation for tangible value. This transition underscores the need for tools that bridge the gap between theoretical potential and practical results. SAS is addressing this challenge with SAS Quantum Lab, a forthcoming environment designed to facilitate hybrid classical-quantum workloads. The lab aims to lower the barriers to entry by providing a platform for exploration, testing, and validation of quantum AI ideas, particularly for users without specialized quantum physics expertise. Current testing indicates the potential for substantial gains; SAS reports performance speedups exceeding 100 times and cost savings reaching 99% through the use of hybrid approaches. The platform, slated for release within SAS Viya in the fourth quarter, will allow side-by-side comparisons of classical, quantum, and hybrid results for various industry use cases. This transition is accompanied by a critical skills gap, with a lack of trained personnel now identified as a significant impediment, highlighting the need for workforce development alongside technological advancement.

The lab will also include a virtual quantum AI tutor to accelerate learning, offering sample code and guidance. “If you’re ready to explore quantum AI, we’re ready to work with you,” added Wisotsky, emphasizing a collaborative approach to realizing the technology’s potential.