Network automation is at the centre of enterprise networking transformation – and is fuelled by artificial intelligence (AI) technology. How does AI influence the future of networking, and why it matters?
Research by virtualisation and networking services provider VMware focused on the impact enterprise AI could have on the future of networking discovered that most modern enterprise networks – as much as 85% – are still dependent on manual processes and outdated configurations, lagging with regards to AI and machine learning capabilities.
Enterprise networking is still hardware-driven, but it has already started to shift to a software-centric approach due to organisations transitioning their data workloads to the cloud to achieve more flexibility and scalability.
With software apps needing to run on on-premises data centres and multiple clouds, the requirements for a different networking configuration have also changed, with the same flexibility and adaptability concept in mind.
VMware talks about networking behaviour – in which networks are configured according to application requirements rather than the physical infrastructure configuration of the past. The infrastructure’s needs are dictated by the way apps interact with data, which can be stored on multiple servers and cloud environments, each with its different requirements.
Enterprise networking is fast becoming the medium of connecting any device and any applications across any cloud environment, merging users, applications and data in the best configuration possible to meet business requirements.
This connectivity is further enhanced by AI functionality, which provides future-forward capabilities and services to applications with wide-reaching potential for networking, increasing network speed and improving the application lifecycle.
Enterprise networking that relies on AI capabilities can improve app behaviour and reaction by recognising patterns and automatically generating actionable insights to correct or enhance the response. It can also assist with security policy development and enforcement and user-related behaviour.
In conclusion, AI-led automation can help solve many challenges such as improving the performance of multi-device IoT connectivity, multi-cloud computing, network integration and applications.
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