As networks evolve and grow, many customers are looking to gain key insight and actionable events from what they learn. Currently, the market is mostly using telemetry data and basic machine learning (ML) to analyze that data. Leading edge cloud providers have gone a step further and are using artificial intelligence (AI) to predict better and adapt networks. The advantage is clear; AI allows networks to operate more efficiently and with higher utilization. I expect to see AI rapidly moving into enterprise and service provider (SP) networks as they adopt AI to enhance their networks and the user experience.
SP networks are about to embrace AI in a big way. The number of devices, led by internet of things (IoT) and edge computing, is about to explode and the ability to apply AI to those networks will allow the human to scale. Over the next several years, the number of IoT devices on the network will surpass the number of human connected devices (smartphones, tablets, etc.). There will be too much data from too many unique sources for humans to be involved much in operating networks going forward. This is especially true with devices that aren’t operating correctly (either hijacked and used for nefarious purposes or broken).
As an example, several vendors today are working with SPs to analyze data flow and system configurations. AI and ML are allowing SPs to see potential issues before pushing new configurations or before an outage occurs. This type of technology is helping make the SP network more robust and reliable as well as enable automation. As AI and ML become more robust, SPs can automatically implement the changes.
In the long-term, AI will automatically change the network, isolate devices and flows, and heal the network without human involvement. This will allow operators to apply human resources more effectively and reduce the cost of running their networks. Imagine a scenario where AI could predict that user experience would degrade in a certain region because of a new latency-sensitive app like augmented reality, and via AI the SP was able to spin up more edge compute resources in that area and reroute the content, so the user didn’t have that degraded experience. This is just the tip of the iceberg on what AI can do, and it will only get more effective with time as it gets more data to learn and train.
In the short term, AI will improve operator efficiency and network performance with a human remaining in the loop to verify or approve the network changes. But operators will quickly learn and rely less on the human.
SPs embracing AI in their networks is an opportunity for the supply chain and will lead to a better consumer experience.