How SAS is approaching AI, quantum, and CX at 50 – Frontier Enterprise

SAS turns 50 this July. As it marks the milestone, the analytics vendor is outlining its next priorities: continued investment in research, internal adoption of generative AI, preparation for practical quantum computing use cases, and continued emphasis on its core analytics business.
In an interview with Frontier Enterprise, Gavin Day, Chief Operating Officer at SAS, and Jennifer Chase, Chief Marketing Officer, discussed how the company is applying its own platforms internally, expanding its work in optimisation and quantum, and reinforcing its presence in Asia-Pacific, where more than half of its revenue is generated outside the United States.
“The people are a critical part of why we’re successful,” Day said, referencing SAS Founder and CEO Dr Jim Goodnight. “We want to make sure we create a work environment and a culture that makes the employees want to drive back onto the campus.”
Noting that SAS Institute was founded on a mission to educate, Day said the journey begins in schools and universities and extends to bringing more people into the technology landscape.
“We have a lot of internal initiatives underway on bringing on younger talent, or people who are changing careers and want to get into the technology space,” he said.
This focus is supported by continued spending on research and development. Day confirmed that SAS intends to keep investing 20% to 30% of its annual budget in R&D.
“Our CTO Bryan Harris talked this year about putting the R back in R&D. There’s been so much development in the enterprise tech space over the last three years, so we’re taking a step back and making sure part of our engineering organisation is focused on research, on topics like quantum, and then looking at how we’re going to use generative AI to make ourselves more productive internally,” Day said.
He added that this investment also informs how SAS approaches prompt engineering to help customers improve the SAS code they write within their own environments.
“If we’re not investing 20%, or 25%, or 30% in R&D, we’re going to fall behind our competition, so we’re going to maintain that level of investment,” Day said.
Chase said her team works closely with SAS’s R&D organisation and positions marketing as the first internal user of platforms such as SAS Viya and CI 360.
“For SAS Viya and for CI 360, we’ve got a broad martech stack that allows us to manage personalised customer journeys at scale, and SAS underpins that. SAS Viya is how we’re pulling in all of our customer data and behavioural data. We’ve got intent data and descriptive data about our customers. We bring all that in, and then we use it to determine which offers to present to customers, with those journeys executed in SAS CI 360,” she said.
Day observed that many organisations are enthusiastic about deploying AI while overlooking the condition of their underlying data.
“Just because you can put something into a pilot or a proof of concept doesn’t mean you’ve done the work to be prepared to flip it over and make it enterprise-scale, with monitoring and all of the things that go around governance,” he said.
Chase added that generative AI amplifies existing data weaknesses.
“Before generative AI, it was garbage in, garbage out. With generative AI, garbage in means garbage scaled,” she said.
“If my data is poor, I’m going to scale a really bad customer experience. I think the more companies start to think like that, the more likely they are to embed trusted processes into their AI adoption,” she said.
At SAS Innovate 2025, the company demonstrated how it addressed a manufacturing problem for P&G using a combination of traditional and quantum computing. Day said he believes quantum computing becoming mainstream is closer than many expect.
“Before, we would have probably said it will still be six years down the road. But now, it is maybe 18 months or two years down the road,” he said.
Drawing a parallel with the early adoption of GPUs, Day noted that not every problem is suited to every type of computing architecture.
“When GPUs came out, we threw every problem we had at them and then realised they weren’t the right tool for many use cases. They were just expensive. For significant optimisation problems, we partnered with Georgia-Pacific to look at how to optimise their manufacturing and plant floors for both efficiency and safety. It’s a huge optimisation problem, and that’s one of the areas where quantum is well suited,” he said.
Day said SAS has been working with the pulp and paper company for over a year.
“Most of the simulation work is done in-house with SAS Data Maker, and then we have relationships with D-Wave and some of the other quantum vendors. Microsoft has put a stake in the ground and said that they’re going to invest there, so we’re partnered with both of them,” he said.
SAS also reaffirmed its commitment to the Asia-Pacific market. Day said that more than 50% of the company’s revenue comes from outside the United States.
“When we think about focus industries, financial services and the public sector are two very big industries for us globally, and the same is true for Asia-Pacific,” he said.
He cited Singapore as a continued growth area in the region, alongside Japan, Australia, New Zealand, Malaysia, Thailand, and South Korea.
“We’re going to continue to grow and continue to invest and focus on our core markets, all the while growing our partner community,” he said.
Even as SAS increases its investment in AI and quantum, Day said the company’s analytics business remains central to its strategy.
“The core analytics business continues to play a critical part in our business strategy. Decision-making depends on being right and being trusted with the math, whether that’s for credit lending, fraud, risk, or patient safety. The foundation of all of that is trust in the analytics, and I think that will remain a huge part of what we do,” he said.

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