How AI and Machine Learning Will Influence the SD-WAN

From sales funnel acceleration to network management automation, artificial intelligence (AI) applications have rapidly emerged as key drivers of business advantage. Gartner ranked “AI and Advanced Machine Learning” as of one of its 10 strategic technology initiatives for 2017, citing a wide range of potential use cases including ones in autonomous vehicles, mesh devices and virtual assistants/advisors. AI in networking is key to a future of automation, since WAN connectivity will need to keep pace if all of these AI-enabled innovations are to reach their full potential.

Chatbots and AI Network Management: Two Sides of AI’s Influence on the WAN

Consider the case of chatbots: These AI-powered programs made headlines when Facebook, among other tech titans, highlighted their utility in streamlining basic online activities such as customer support and ticket purchases. In highly specific realms such as customer relationship management (CRM), an AI chatbot can also potentially automate the bulk of all interactions, saving tons of time for busy employees.

AI and machine learning in networking have become more useful as WAN requirements have evolved. For example, several telecoms in Europe and North America have already explored AI network management for tasks such as WAN path optimization, fault prediction and greater distribution of network intelligence to the edge. Similarly, the SLAC National Accelerator Laboratory is using a grant from the U.S. Department of Energy to explore resiliency improvements in its network, such as detecting outages more quickly, according to Metering & Smart Energy International.At the same time, many of the CRM platforms and other software solutions that may incorporate chatbots and additional AI functionality are reshaping WAN traffic. For example, real-time updates are essential to a chatbot conversation, but traditional hub-and-spoke WANs weren’t built with AI applications in mind. They cannot deliver the necessary agility, cost-effectiveness or Quality of Service (QoS):Enter software defined WANs (SD-WANs) as well as AI network management.

In these ways, the spread of machine learning and AI in networking simply reinforce and extend existing SD-WAN features. Modern SD-WAN providers can deliver a software-driven WAN fabric with centralized control and visibility, a unified pool of bandwidth and rapid deployment – all pivotal advantages when incorporating AI applications into the network.

SD-WAN for AI Application and the Internet of Things

The combination of SD-WAN evolution and AI network management will support new classes of highly demanding applications, whether they are powered by AI, part of the Internet of Things (IoT) or both. Thanks to their app-awareness, SD-WANs can create dedicated QoS lanes for the most mission-critical traffic, avoiding congestion by shifting traffic dynamically across multiple links. These links can even be commodity Internet – a major win for scalability and affordability compared to MPLS lines alone.

The advance of AI in networking will offer synergistic benefits. With edge traffic complexity and volume increasing as AI and IoT applications traverse clouds, data centers and branch offices, having a reliable SD-WAN provider is more important than ever. Learn more about Talari’s SD-WAN solutions by visiting our demo page, where you can also contact us directly.

Categories: Software Defined WAN (SD-WAN), Application Performance/Application Quality, Network Reliability, Internet as WAN (MPLS Alternatives), Enhance WAN Optimization, Intelligent WAN