Can AI Help Network Staffs Manage Network Complexity?
As IoT, cloud-based, and on-premises networks converge, data on network performance is pouring in from all points. How can network staffs keep up? Is there a place for AI in network monitoring, and where should you draw the line?
Between now and 2032, the IoT (Internet of Things) market is expected to grow by a CAGR of 24.3%, reaching $4,062.34 billion by 2032. The primary growth drivers are the movement of more business operations to remote locations, the ability of more powerful IoT devices to do more IT on their own, and the ability of IoT to find a place in almost every business use case that companies develop.
At the same time, new network protocols like Wi-Fi 6 are dramatically increasing the number of devices that networks can carry.
Both trends lay the groundwork for corporate network expansions, but the complexity of having to monitor all of these network nodes and devices also expands exponentially for network staffs. Even with current network monitoring and remediation tools, how will network professionals be able to catch every emerging performance or security issue?
The industry answer is by adopting artificial intelligence (AI) for network monitoring, maintenance, and remediation. AI has the potential to automate a large share of work in these areas that staff must do manually today—with the added advantage of being able to rapidly process and assess incoming real time data so the AI can act quickly. This is what makes AI a key component of AIOps (AI for IT operations).