Every company wants the power of insights-driven by machine learning and artificial intelligence. But like any complex undertaking, making that wish a reality involves specialized expertise and a lot of investment … unless someone else will do the heavy-lifting for you.

“What Amazon continues to do is make [AI/ML] easier to consume by the developer, by the customer, and to embed into applications,” said Chris Wegmann (pictured, right), managing director of the Accenture AWS Business Group at Accenture.

Wegmann and Brian Bohan (pictured, left), director and global head for the Accenture AWS Business Group at Amazon Web Services Inc., spoke with John Furrier, host of theCUBE, SiliconANGLE Media’s livestreaming studio, during the AWS Executive Summit. They discussed business technology vision and the many announcements made during AWS re:Invent 2020. (* Disclosure below.)

Re:Invent 2020 marks the year of embedded intelligence

From the Amazon Connect omnichannel cloud contact center to the SAP Data Lake Accelerator, re:Invent 2020 was filled with intelligent products.

“How many announcements were there where machine learning is just embedded in? I mean, CodeGuru, DevOps Guru, Panorama … it’s just there,” Bohan said.

By embedding intelligence into its products, AWS is making AI/ML easier to consume and shortening the development process by reducing the amount of work the developers need to do.

“I keep coming back to AWS, and cloud makes it easier,” Wegmann stated. “I think you’re going to see more and more of these multi-connected services by AWS that have a lot of the AI/ML preconfigured data lakes, all that kind of stuff embedded in those services so you don’t have to do it yourself and continue to go up the stack.”

AWS has an advantage in the market, as many companies already subscribe to its services and store their data in the company’s cloud.

“That’s the power of bringing it together on AWS,” Wegmann said. “The access to all those different capabilities and services and then also where the data is, and pulling all that together for that end-to-end view.”

AWS customers no longer have to make trade-offs, according to Bohan. “They can really deploy natively in the cloud, and then they can take those capabilities, train those models, and then deploy them where they need to — whether that’s on-premises or at the edge, whether it be in a factory or retail environment.”

Cloud is complex; hybrid edge cloud is complexity compounded

Simplifying the complexity becomes even more important when you have hybrid edge operating with microservices on a cloud model, Furrier pointed out.

“I don’t even know what to call the cloud anymore,” Wegmann said. “I’ve got a big cloud which is central, but go down and you’ve got a cloud at the edge. So what do I call that?”

Getting customers to the cloud is the priority of the AWS and Accenture partnership, according to Bohan. This is because it’s only once they are there that the possibilities opened by access to AWS services and common data capabilities can be leveraged.

“Permeated through this week at re:Invent is that opportunity, especially in those industries that do have an industrial aspect, a manufacturing aspect, or a really strong physical aspect of bringing together information technology and operational technology and the business with all these capabilities,” Bohan said. “And I think edge [computing], and pushing ML down to the edge and analytics at the edge, is going to help us do that.”

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

Photo: SiliconANGLE