With the public release of ChatGPT and Microsoft’s $10-billion investment into OpenAI, artificial intelligence (AI) is rapidly getting mainstream approval. For business networking specialists, this implies there is a very real possibility that AI traffic will affect their networks in major methods, both favorable and negative.As AI becomes
a core feature in mission-critical software application, how should network teams and networking professionals get used to stay ahead of the trend?Andrew Coward
, GM of Software Defined Networking at IBM, argues that the enterprise has actually already lost control of its networks. The shift to the cloud has left the standard business network stranded, and AI and automation are required if business intend to regain control.
“The center of mass has shifted from the business information center to a hybrid multicloud environment, however the network was created for a world where all traffic still flows to the information center. This indicates that a number of the network components that dictate traffic flow and policy are now beyond the reach and control of the enterprise’s networking groups,” Coward said.Recent research from Business Management Associates (EMA)supports Coward’s observations. According to EMA’s 2022 Network Management Megatrends report, while 99%of enterprises have adopted at least one public-cloud service and 72%have a multicloud technique, only 18% of the 400 IT organizations surveyed believed that their existing tools are effective at keeping an eye on public clouds. AI can help keep an eye on networks.AI is worrying networks in
both obvious and nonobvious ways
. It’s obvious that organizations that utilize cloud-based AI tools, such as OpenAI, IBM Watson, or AWS DeepLens, need to accommodate rush hour between cloud and enterprise data centers to train the tools. Training AI and keeping it present requires shuttling enormous quantities of information backward and forward. What’s less obvious is that AI enters the business through side doors, sneaking in through capabilities
built into other tools. AI includes intelligence to everything from content production tools to anti-spam engines to video security software application to edge devices, and a number of those tools constantly interact over the WAN to enterprise data centers. This can create traffic rises and latency concerns, among a variety of other problems.On the positive side of the ledger, AI-powered traffic-management and tracking tools are starting to help resource-constrained network teams handle the intricacy and fragility of multi-cloud, distributed networks. At the very same time, contemporary network services such as SD-WAN, SASE, and 5G also now count on AI for such things as intelligent routing, load balancing, and network slicing. But as AI takes control of more network functions, is it wise for business leaders to trust this technology?Is it wise to trust AI for mission-critical networking?The experts who will be charged with using AI to make it possible for next-generation networking are not surprisingly skeptical of the lots of overheated claims of AI suppliers.
“Network operations handle what lots of view to be a complex, vulnerable
environment. So, many groups are afraid of using AI to drive decision-making due to the fact that of potential network disruptions,”stated Jason Normandin, a netops product manager for Broadcom Software.Operation teams that don’t comprehend or have access to the underlying AI model’s reasoning will be tough to win over. “To ensure buy-in from network operations teams, it is critical to keep human oversight over the AI-enabled devices and systems,”Normandin stated. To rely on AI, networking experts require”explainable AI,”or AI that is not a black … Source
