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The justification for HPE buying Juniper may be a mundane, economy-of-scale play or a move to gain Juniper's AI networking technology. Or there may be a vision for something more ambitious.
Enterprises see the potential for AI to benefit network management, but progress so far is limited by AI’s ability to work with company-specific network data and the range of devices that AI can see.
Using generative AI technology for network operations issues can yield results that sound credible but are actually completely wrong.
Volume of data, frequency of polling, security, and the impact on network performance are among the concerns of networking teams, according to an EMA survey.
Infusing a network organization with artificial intelligence will involve offloading tasks to AI, changing your approach to skills development, and as staffing requirements change, displacing workers.
There are lots of good reasons for network automation, but network teams need to be mindful of what they want to do with any time and resources saved.
Network observability can be dismissed as a buzzword, but to be useful it should include monitoring, security, data, and actionable insights.
Artificial intelligence and AI vendors promise a lot, but grill your providers about how theirs works and its limitations.
EMA study found networking pros who reported the most success with AIOps pointed to improved security and compliance as a potential benefit.
Automation tools can reduce manual tasks and improve security today even though the goal of full automation is still remote.
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