While many people think of artificial intelligence on the consumer level — like the Siri virtual assistant from Apple Inc. — the way AI should be looks very different on the business level.

So how exactly is AI different for business versus the consumer? Scott Hebner (pictured), vice president and chief marketing officer of IBM Data & AI (Watson) at IBM, reveals business versus consumer AI and four core attributes.

“When we talk about AI for business, we’re thinking about four core attributes,” Hebner said. “Those four … attributes come together to what we call AI for business — and that’s what’s going to allow call centers, and supply chains, and business planning, and risk and regulatory … mitigation … those kinds of things to really come to life in a predictive way.”

So what are the four core attributes of AI for business? Hebner spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during IBM Think. They discussed the four core attributes of AI for business. (* Disclosure below.)

Language, automation, trust and integration

The first core attribute is that AI for business needs to understand the unique language of a company’s business and industry, according to Hebner. Within this, there is the necessity to have the ability to really understand the context of language.

“That’s not just natural language, but it’s the ability to debate, it’s the ability to read documents, interpret documents,” Hebner said. “You and I can ask the same question in five or six different ways, and it needs to understand the business to be able to interpret that and help answer the question. Unlike like Siri or Alexa, where you’ve really got to have the right semantics and they won’t understand the nuances.”

The second core principal is that AI must be the engine for automation. This is because if AI is really about automating workflows and experiences, anything that a company wants to automate and make more productive will need to have some predictive capabilities to it.

The third core attribute is about driving trust and positive, healthy business outcomes through AI, according to Hebner. AI should be able to explain to a customer convincingly why they should do something, because explainability and trust is such a critical part of AI for business.

Finally, the fourth core attribute is that “it needs to run everywhere. It has to integrate everything,” Hebner stated. “Unlike a lot of the competitors where you have to bring the data to AI, we’re saying leave the data where it lives and bring AI to the data. So it runs anywhere from the data center to the edge — the same model, the same capabilities in a distributed environment.”

All of this means that data must be the lifeblood of AI. IBM is helping find solutions to these attributes by bringing together a fully unified data and AI platform through its IBM Watson products and services.

“The average large enterprise has over a thousand repositories and sources of data. As things go out into the edge, that’s just sort of multiplying,” Hebner concluded. “There’s more and more movement to put applications … software-as-a-service applications on the cloud, and most businesses have multiple clouds.”

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of IBM Think. (* Disclosure: TheCUBE is a paid media partner for IBM Think. Neither IBM, the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE