Cisco's AI Summit kicked off last week with a speech from CEO Chuck Robbins and Chief Product Officer (CPO) Jeetu Patel outlining how they view speed in deploying AI and the underpinning infrastructure crucial for enterprises moving forward in this area.
"Our recent survey said only 13% of our enterprise customers feel like they really have a grip on what they're going to do with AI, but they all know they have to get a grip on it,"
Robbins said.
"They also are balanced with the risk and concern of being left behind by some competitor figuring out faster than they do."
Not only did it give some big product launches, like the AI Defense solution, but it gave us a clue as to what Cisco sees as the future of its AI drive and how that can play into its products.
Key Ideas in AI Vision
Robbins' talks on speed and agility came underpinned by what Cisco announced they are broadly focusing on to bring these AI services to its customers.
Having already led the company for nine years as CEO, Robbins is no stranger to the effort it takes to integrate whole new systems on scale.
In 2015, Cisco began its transition to feature greater capabilities in the then-emerging technology of cloud computing.
Yet, just like at that time, users would focus on adoption for adoption's sake rather than as part of any strategic initiative.
"Customers would tell me, and CIOs would tell me, I'm just signing up for Office 365, so I can tell our CEO we're in the Cloud, get off my back," Robbins said. "I think we have similar pressure now, but with a much greater understanding from the C-suite."
He went on to explain his belief that the service provider community is thinking hard about what their role is relative to the enterprise deployment of AI.
As Patel joined him on the stage for the keynote, the areas of interest took shape in which the CPO summarised would form 'three specific areas' for Cisco.
"We are gonna have a great set of services from Cisco that'll really help organisations get up and running fast,"
Jeetu said.
One was infrastructure, so the computing and networks needed to build new AI applications and use cases.
Another is tooling: the ability for organisations to ensure that they are digitally resilient to stay up and running.
And finally, security. "I think there's going to be a huge amount of demand for making sure that we have a consistent way of applying safety and security across the entire state for AI," Patel explained.
