Over the past few years, companies have had to adapt to remote work environments, hybrid work environments and everything in between. Organizations across industries managed the transition by accelerating digital transformation efforts, rapidly adopting new tools and technologies.
While this combination of new technologies has streamlined processes and enabled hybrid work for many employees, a reliance on cloud services and new models of working mean there is more for IT teams to manage than ever – and less time to do it. Research from analyst firm ESG shows that 91% of IT professionals believe their organization needs to move faster. At a time when IT hiring has never been more difficult, this is far easier said than done. The WAN is one area that has become especially difficult for teams to manage.
Managing the WAN traditionally has been one of the most time-intensive aspects of running an enterprise network. SD-WAN has gone part of the way towards easing this burden. SD-WAN uses programmable network devices that IT Teams can modify remotely and through dynamic best-path routing, both of which improve cost, agility, and performance by proactively responding to real-time network conditions. However, with the increased demands placed on IT teams by ever-increasing adoption of new digital tools, teams must find new ways to continue streamlining management of networks, including the WAN. AI can provide the answer.
The impact of virtual network assistants
While āchatbotsā have a mixed perception, many enterprise IT and networking teams have already recognized that advances in natural language understanding (NLU) and AI are empowering the next level of conversational interfaces and new virtual network assistants (VNAs) have been developed that can deliver more than basic information or canned responses. Advanced VNAs powered by AI can provide teams with actionable insights and problem-solving recommendations from an informed perspective.
Even beyond just conversational dialogue, VNAs are becoming capable of proactively identifying service-impacting events, determining the root cause, and offering auto-remediation or suggested steps to resolution. The ability for teams to offload some fixes onto an automated tool like a VNA can go a long way towards alleviating workload and improving management of the network as a whole.
This is particularly beneficial when it comes to problems with SD-WAN. The SD-WAN is a complex structure with many components. If, for example there is a bad cable connection somewhere within the network that is causing intermittent problems for users, teams could spend enormous amounts of time working through a checklist of possible problems including both software and hardware before physically checking cables. A VNA with integrated AI can actively monitor the network and pinpoint problems, functionally completed that initial checklist by itself, so teams are notified of a bad cable before time is wasted elsewhere. (For example, Juniper Mist AI uses the decision tree machine learning algorithm to identify bad WAN cables.)
Simplifying solutions
While SD-WAN can reduce the cost and experience for users, it is unquestionably more complex from an operations standpoint. When things go wrong with the network, the increased complexity caused by the integration of SD-WAN can cause mean time to resolution to skyrocket. Much of this complexity can be alleviated with AI.
When users are experiencing lag time or dropped connections, an IT team normally needs to manually
check each user device, investigate each wireless and hardwired connection and even walk around the office area trying to narrow down the location where the loss is occurring. At a time where on-site crews are smaller than ever due to the increase in remote work these fixes can be exceedingly time consuming and difficult.
However, AI tools integrated into the network can handle the issue identification process, so teams are directed to the problem immediately, allowing them to repair the user experience sooner and use their valuable time for tasks more important to the organization. It could even allow IT leaders to reduce their on-site staff, opening new doors for remote team members, widening the hiring pool, and offering flexibility that traditional competitors canāt match.
An easier-to-manage network
Even when things are proceeding as planned, the increased information it can provide about the network and its performance can easily become a flood of complex data points that are difficult for teams to parse or draw insights from. AI is the perfect solution.
By leveraging a full stack AI-platform to manage every aspect of the network, including SD-WAN, IT teams can streamline their processes and focus on the work that really matters, improving IT and end user experience and saving organizations time and money. Implementing the next level of AI, including VNAs, into the enterprise will unlock doors to enhanced productivity and insights; significantly decreasing user-generated IT tickets, allowing teams to fully realize the potential of SD-WAN.
