What You Need to Know About Predictive Network Technology

It's almost like magic, but predictive network technology is anything but a trick.

Using artificial intelligence (AI) and machine language (ML) mathematical models and algorithms, predictive network technology alerts an organization to network issues as early as possible and offers problem-solving solutions. "The technology enables networks to learn from past instances using massive amounts of data through predictive analytics," explains Titus M, a senior analyst with technology and business research firm Everest Group. "It collects network telemetry data, recognizes trends, and forecasts network difficulties that might negatively impact user experience and offers potential solutions to the issue."

Predictive network technology can also suggest network remediation solutions for automatic or manual implementation, depending on the use case, at the discretion of the IT networking or operation team, says Sam Halabi, technology consulting competency leader at business advisory firm EY.

Predictive network technology's value is that it helps network operations transition from a reactive to a proactive model when it comes to addressing potential issues. "Network problems can happen due to many factors, such as degradation in the transport network, bandwidth congestion/traffic loss, suboptimal routing, network outages, and so on," Halabi says. "Such problems are very disruptive to the business and can have a major negative financial impact when they occur."

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Challenges and opportunities

Although a powerful and beneficial tool, predictive network technology presents some serious risks. One concern is that the system can only make decisions based on available options. "If you haven't planned for it or have not trained it for certain situations, the system might not be able to respond appropriately," says Chuck Everette, director of cybersecurity advocacy at Deep Instinct, a cybersecurity technology company. Everette reports he has witnessed situations "where automated decisions were happening at such a pace you couldn't make heads or tails of the root cause due to the constant changes in the adaptation of the network trying to fix or heal itself."

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