As the generative artificial intelligence wave continues to revolutionize the technology industry, there’s been a very important question to answer — who has the goods, and who is A-washing? The distinction is very simple: It involves zeroing in on who can take something from data to decisions, including in the realm of industry-specific AI. that’s where SAS Institute Inc. and its focus on industry-specific AI comes into play, according to Ray Wang, founder and principal analyst of Constellation Research Inc., who spoke with theCUBE during the SAS Innovate event. What the company has been showing is where models come into play and what one can do with the data.

“These guys are steeped in this. We’re talking like decades of experience. What they’re trying to do here is package it, so it’s going to be simple for customers to use,” Wang said. “It’s been one of the things that has been burning SAS for a long time. They’ve been seen as the legacy analytics company. They’re slow to make a move. But you know what? It’s in their benefit right now.”

The central message of the recent SAS Innovate event was that SAS, with all of its knowledge, is trying to make it easier for people to use AI. For SAS, it means establishing a focus on industry-specific AI while outlining the necessary products and processes along the way.

This feature is part of theCUBE’s special coverage as part of SAS Innovate. (* Disclosure below.)

Advancements in SAS Viya and AI integration

Key to understanding SAS’ strategy means understanding updates to the company’s Viya artificial intelligence and analytics platform. In September 2023, the company amped up development features in Viya and said users of its customer relationship management application Customer Intelligence 360 would be able to integrate with their choice of generative AI models for use in marketing planning, content creation and journey design.

SAS further outlined its plans for SAS Viya in April 2024. At that time, the company announced new industry-specific generative AI assistants, a new developer platform called SAS Viya Workbench, and a new synthetic data generator called SAS Data Maker. The company introduced a new Viya Copilot offering for developers, data scientists and business users, which the company said would help with everything from administrative analytics tasks to solving industry-specific business problems.

SAS said that Viya Copilot could help simplify code compilation, speed up the code commenting process and create streamlined code interpretation. Andy Thurai, vice president and principal analyst at Constellation Research Inc., said at the time of the announcement that Copilot could help users manage multiple tasks and be particularly useful for knowledge gap analysis and data wrangling tasks.

“This could be useful in reducing the need to perform manual tasks where data scientists spend much of their time,” he said.

At SAS Innovate 2024, the company also provided more information when it came to its SAS Data Maker, which it describes as a trusted synthetic data generation experience. SAS Data Maker allows the company to attack the gap in structured data for synthetic data, according to Bryan Harris, chief technology officer of SAS.

“By being able to do that, we can go into regulated spaces and give proof to the statistical congruence of synthetic data that can bootstrap models that will allow them to run effectively on real-world data,” Harris told theCUBE.

Over the next year, solutions are anticipated to be built with SAS App Factory, a rapid application development environment for creating AI-driven applications. The productivity of that product is notable, according to Harris.

“We started wrapping some generative AI experiences on building applications … the treatment on that’s going to be incredible,” he said. “I think what you’re going to see on our Viya Copilot … the ability for our Viya Copilot to be a very practical approach to the AI lifecycle, I think it’s going to be world-class and second to none.”

SAS’s go-to-market strategy amid a changing landscape

For companies that are considering potential IPOs while integrating AI, there’s clearly much to consider in this new environment. To get from point A to point B, one must consider one’s AI story, according to Wang. For SAS, the company must show subscription revenue growth as they’ve been going from on-prem to cloud, according to Wang. That’s one of the company’s big challenges.

“They’ve actually been showing growth with Viya,” he said. “The third thing really is they have to show that they’ve got a management team that goes beyond [Jim Goodnight, cofounder and chief executive officer of SAS]. They’ve been doing that. They’ve removed and replaced a lot of people along the way.”

When it comes to the go-to-market for SAS, it involves a focus on partnerships and ecosystem, according to theCUBE Research’s Principal Analyst Rob Strechay. That’s a crucial part of the months ahead.

“They really need to jump in, full-on, with that, because I think part of that will help them in that runway to get to repeatability, that ARR, and give them that runway that gets them the eight-plus quarters of successive growth,” Strechay said.

This conversation is growing in importance given the landscape in Silicon Valley today, with a series of layoffs being among the big stories of the year. For SAS, responding means an emphasis on getting AI into the hands of the people.

“AI really gives them a real accelerated tailwind to modernize and get a new opportunity to reshape their brand,” said John Furrier, executive analyst with theCUBE Research. “Because, look. Let’s face it. You don’t want to be your grandfather’s tool from the 90s, or 80s, or even 40 years ago. But they have all the data.”

Industry-specific AI a key plank in SAS’ future

As SAS Innovate 2024 drew to a close, the company’s vision for industry-specific AI integration became more clear. SAS Viya is the centerpiece for the company’s long-term AI strategy, while SAS is seeking to leverage its nearly 50 years of expertise to simplify AI applications.

At some point, companies need to integrate all technology, according to Harris. What one is really getting to is making a final decision to give a response back to a user.

“As we know, a lot of these use cases right now are very shallow. They’re just prompt engineering to an LLM and come back,” Harris said. “Yes, RAG architectures are there, but we’ve got to get things done in sub-second response times here. There’s very, very challenging integration and expectations of responses from generative AI workflows that we have to get done.”

That’s where Viya comes into play. The goal is to bring all of the aforementioned details together, Harris added.

“We can augment prompts, we can orchestrate against other traditional models and things like that and bring that data back in so that the LLM can reason over that and send back the response back to the user,” Harris said.

All told, SAS has outlined its goal for industry-specific AI integration and its advanced AI models. Eventually, the company will sell “Lego blocks of models” to be applied across different scenarios and industries, according to Furrier.

“We’ve been seeing on theCUBE that the data science world is shrinking … in terms of core people,” Furrier said. “You don’t have to be a data scientist, you don’t have to be in the game with generative AI. You can be a user. And the democratization wave that’s coming in … is very clear in the data.”

(* Disclosure: TheCUBE is a paid media partner for SAS Innovate. No sponsors have editorial control over content on theCUBE or SiliconANGLE.)

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