Given Hewlett Packard Enterprise Co.‘s Juniper acquisition has now had a bit of time to percolate, I was expecting to see at HPE’s European version of its user event Discover this week in Barcelona how it’s using the combined assets to reshape itself for the artificial intelligence era. The event is the first real glimpse into how the Juniper Networks acquisition is taking shape, just five months after the deal closed.
Artificial intelligence is at the heart of almost every part of an organization’s strategy, and that includes information technology operations. However, many organizations aren’t seeing clear business results. In fact, a recent MIT Study found that 95% of generative AI projects are failing. One of the big reasons for failure is that AI is being deployed in silos resulting in partial insights into the broader ecosystem.
Now that Hewlett Packard Enterprise Co. and Juniper Networks Inc. this weekend settled with the U.S. Department of Justice, the $14 billion deal that will bring Juniper’s networking and security assets into the HPE portfolio will enable HPE to continue its transformation to a networking-first company. Many industry watchers, me included, had started to wonder if any agreement could be reached prior to the upcoming July 9 court date.
Juniper Networks Inc. is focusing on helping customers move artificial intelligence in their networks from vision to reality, and today it laid out its plans at its AI-Native NOW customer event at the New York Stock Exchange. Over the last several years, Juniper has developed strong AI networking products, and interest in AI for networking is extremely high, as engineers need help keeping up with modern networks’ complexity.
There has been plenty of hype and ballyhoo around artificial intelligence and networking, but much of the vendor focus has been AI for networking, where AI is used to improve network operations. The other side of the AI coin is networking for AI, where a network must be designed and provisioned to support an AI implementation. Though many businesses will likely deploy AI in the cloud, making the supporting network the problem of the hyperscaler, 58% of respondents to a recent ZK Research/theCube Research study stated they have deployed or will be deploying AI in their own private data center.