As it moves to embed artificial intelligence and machine learning throughout its product line, SAS executives say the company will look to its growing base of partners to bring domain expertise to make that artificial intelligence actually intelligent.
At its Global Forum event in Denver last week, the company announced that AI would become a common feature across its offerings. And CMO Randy Guard told ChannelBuzz.ca at the event that the biggest untapped opportunity for the company’s partners is in connecting that AI capability with their own knowledge.
“If you’re going to solve a problem an AI product, you’ve got to bring your domain expertise, and marry the two of those together,” Guard said. “As we start embedding AI and intelligence in everything we do, our partner community needs to recognize how that can be applied to the business scenarios they’re solving for their customers.”
The idea of partners adding value by connecting AI or machine learning with their own set of business skills has been a common thread in the industry this year, with IBM making similar comments about how partners can maximize the opportunity around their Watson platform at last month’s Think conference.
Oliver Schabenberger, COO and CTO of SAS, spent much of his keynote time at Global Forum seeking to educate his audience — the analytics software company’s users and partners — on its AI strategy, and also preemptively looking to reduce customers’ fears around what the rise of AI might mean for their careers are the builders of analytics algorithms and interpreters of analytics results. Humans have no need to fear AI, he assured the audience.
“We sometimes confuse automation with autonomy, and we attribute too much intelligence to AI, and the capacity to reason,” Schabenberger said. “That amplifies our fear of losing control, but the fact that remains that behind every algorithm, behind every automated system, is one or more person.”
In a briefing with press, he elaborated on the idea that where AI shines is not in reasoning, but in automating systems — be they very finite and simple, or broad and complex. He also advocated for the role of AI as “a second set of eyes” — used, for example, in healthcare to recognize patterns doctors may not, prioritizing cases for doctors, or backing up a diagnosis made by a human doctor.
He also promoted the ability of learning systems to level playing fields in business — for example, the opportunity for a small “local” business to go international much more seamlessly by auto-translation of their content and context in any language a potential customer may work in, on the fly.
“It’s about augmentation and automation,” he said.