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.
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.
Juniper Networks today announced several new features and products that bolster its AI-driven networking capabilities. The company has extended its Mist technology to operate across the wired network, data center and, most recently, SD-WAN.
The concept of AIops is simple: Infuse artificial intelligence(AI) into IT to make operations speedier and more efficient. In theory, AIops at its best should lead to an autonomous IT environment in which functions can run themselves with little or no human intervention. In practicality, the path to this nirvana state is anything but straightforward and raises several questions. Where should you start? How do you measure the value? Is AI ready to scale across production environments? Do I need new tools?