How artificial intelligence can support lean IT teams

Juniper Networks Australia

By Bruce Bennie, VP & GM, ANZ, Juniper Networks
Tuesday, 16 November, 2021

How artificial intelligence can support lean IT teams

The last two years have seen an accelerated shift to digital working and, in turn, a continued rise in the adoption of new technologies.

A recent survey showed that more than seven in 10 (71%) IT professionals in APAC who are directly involved in AI and machine learning deployment within their organisation strongly agree that digital technology is changing the way we operate in our day to day. They also believe digital technology and AI will “become the new co-workers of the future” — this is compared to only 54% in North America.

The use of, and trust in, artificial intelligence is rapidly accelerating in the APAC region, with more than two in five (42%) respondents reporting that 50% or more of their operational decisions are currently assisted by AI decisioning or will be in the near future.

While the potential benefits of AI span far and wide, one area that the technology is having an immense impact on is networks. AI-driven networks are not only enabling large enterprises to improve their customer and employee experiences, they are also helping smaller organisations with lean IT teams and limited technological resources to do the same and benefit from better, more intuitive networks.

The power of AI-driven networks

Many organisations across the country, from schools to startups, have IT teams that are often composed of only a few individuals. While they may be very skilled practitioners, maintaining a traditional network is time-consuming. AI-driven networks can help these leaner IT teams to focus on priority items by automating tasks to reduce workload, allowing them to dedicate their limited time and resources to more impactful tasks.

AI-driven networks can dynamically adjust bandwidth, self-correct for maximum uptime and quickly find root causes. They even allow operators to understand and interpret the vast amounts of available data to improve the experience of those on the network, avoiding the need to exhaust their time and energy simply maintaining it.

Cutting vital costs

AI can also be key in lowering costs for IT teams. Proactive automation of tasks such as issue detection and analysis allows traditionally time-intensive tasks to be addressed automatically, reducing person-hours.

For example, if a network user’s video call suddenly drops, it could be due to an unstable Wi-Fi connection, a bad Ethernet cable on their router, a fault within the application server or malware on their computer, just to name a few. AI-driven networks can find the issue and resolve it before the user even knows there is a problem — something which would traditionally cost IT departments hours of manual investigation.

How does this all work?

To be successful, AI requires machine learning, which is the use of algorithms to examine and analyse data, learn from it and make a prediction. Thanks to significant computational advances, machine learning has evolved into more complex models such as deep learning, which uses neural networks to provide even greater insight and automation.

While machine learning leads to networks being able to make predictions and suggest best actions, deep learning allows a network to apply additional layers of thought, ultimately creating a self-driving system. Both are vital components of AI-driven networks.

Advancements have also been made in natural language processing, allowing companies like Juniper Networks to develop network assistants: AI-driven tools that offer a conversational interface to IT teams and network managers to detect and resolve network issues.

For example, typing in “show unhappy users” will prompt the network assistant to show any devices connected to the network that are having connectivity issues. Network operators can then click through to troubleshoot the issue directly from their laptop, thanks to the power of AI.

The way forward

While AI-driven networks are already incredibly advanced, and adoption of AI remains significant in the APAC region, there are no signs of things slowing down. In the future, AI will be able to go as far as predicting a user’s internet usage, making it possible to dynamically adjust bandwidth capacity to maximise overall performance.

As it stands, however, AI is already leading the charge in enabling even the smallest of IT teams to operate high-performing, intuitive networks and powering seamless experiences — all while saving costs and enabling IT staff to focus on the tasks that matter.

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