Even though generative artificial intelligence is taking the world by storm, enterprises are looking at the bigger picture of how it can drive real value.

As a Fortune 500 company that offers financial protection to millions of customers and policyholders, Aflac Inc. leverages DataRobot Inc.’s end-to-end AI and machine learning lifecycle platform to drive real business value through the power of prediction, according to Sarah Gibson (pictured, left), analytics manager at Aflac

“We’ve been able to leverage DataRobot to help improve projections and fraudulent data.” Gibson said. “DataRobot gives us prediction explanations, which helps drive our users in the direction we think is best fit for them. Within the last couple of years, we’ve been using Snowflake to now pull the data from DataRobot using an API and then pushing our results and our predictions back into Snowflake from DataRobot.”

Gibson and Lisa Aguilar (right), vice president of product marketing and industry CTOs at DataRobot, spoke with industry analysts Lisa Martin and Dave Vellante at Snowflake Summit, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how Aflac uses value-driven AI for enhanced business outcomes with the help of DataRobot and Snowflake Inc. (* Disclosure below.)

Unlocking business value with generative and predictive AI

Generative AI – think ChatGPT – has played an instrumental role in making the AI concept go mainstream. Nevertheless, generative AI’s significant potential can be realized if it’s coupled with predictive AI, according to Aguilar.

“I think the way that we look at it as generative AI is an incredible technology, but what makes it extremely powerful is when you can add in the predictive AI as part of it,” she noted. “If you’re in a real business, like with Aflac, and you’re trying to understand who are my best customers to make sure that we want to make sure that we understand … that’s where the power of prediction actually comes in.”

Since generative AI is powerful, setting up the large language models behind it properly is of the essence for brand reputation. DataRobot helps with this objective through its expertise and methodical approach because it eliminates hallucinations by narrowing down the vector database, Aguilar pointed out.

“If you’re looking at embracing it as an actual technology, it’s much better to be very methodical and slow because there is a brand reputation risk,” she pointed out. “You don’t want it to come up with an answer just because it can. We’ve curated that expertise over hundreds of thousands of use cases so we can help provide those guardrails and recommendations.”

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of Snowflake Summit:

(* Disclosure: Snowflake Inc. and DataRobot Inc. sponsored this segment of theCUBE. Neither Snowflake, DataRobot, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE