Artificial Intelligence (AI) has been making headlines since it went mainstream in 2023. Between June 2022 and March 2023, the traffic volume for the keyword “AI” tripled, rising from 7.9 million monthly searches to more than 30.4 million. But as AI is becoming a bigger part of our daily lives, we are also learning to tell the difference between real AI breakthroughs and those that form just another wave of hype. One place where AI is definitely not hype and where it is making a real, tangible difference is in network as a service (NaaS) deployments in enterprise networks.
AI is fundamentally changing how businesses manage their networks, making NaaS much more efficient and accessible. We believe in 2025, this will drive broader NaaS implementations across enterprise verticals and solve one of their biggest challenges – IT staffing shortages.
The role of NaaS in modern businesses
NaaS is essentially a cloud model that enables businesses to easily operate the network from a cloud vendor instead of setting up their own network infrastructure. This allows enterprises to subscribe to the service rather than invest in their own hardware and IT teams. In the NaaS model, the provider monitors, manages ad optimises the enterprise’s network via software over the internet, potentially replacing on-site hardware as well. What’s more, NaaS represents a significant shift from networking-first thinking to a deeper focus on the user-end experience. SLAs (Service Level Agreement) become even more important in NaaS since the primary metric for enterprises is the user experience.
The NaaS business model holds a number of advantages to enterprises, the biggest being its economic benefits. Primarily, the model eliminates the need for large IT departments and provides built-in security by integrating cybersecurity measures directly into the network. This allows business to scale by adjusting network configuration through software rather than physical hardware upgrades. Overall, these benefits allow enterprises to concentrate on core business activities.
Despite the benefits, many businesses have been hesitant to adopt NaaS, primarily due to concerns over the lack of effective tools to gain insights and maintain precise network control with a small, cost-efficient IT team. NaaS solutions have never been truly hands-off or effortless, and skilled professionals are still required to oversee the process, but cost-efficient expertise is hard to find. However, we have seen that this changing, with 55% of large enterprises holding a substantial majority in NaaS market share and 90% of businesses predicted to incorporate some form of NaaS into their networks by 2030.
AI is transforming NaaS
With both current and upcoming AI integrations, AI is well positioned to take NaaS capabilities, efficiency and economy to reach new heights by addressing these persistent challenges – and this begins with understanding the enterprise’s main concerns.
To begin with, AI integration enables a future-ready NaaS deployment, assuring streamlined upgrade cycles in the network. However, enterprises are now facing much more advanced technology managed by fewer staff, stricter SLAs and scare IT expertise – driving up costs and risks without directly benefiting core products.
One of the biggest challenges enterprises face today is the shortage of skilled IT professionals. With networks becoming increasingly complex due to multiple layered technologies like Wi-Fi, private cellular, Zigbee and Bluetooth, enterprises are struggling. Each of these technologies connects to an ever-growing number of devices and applications, creating a tangled web that even the most experienced IT professional would struggle to manage.
AI-powered NaaS simplifies this problem. Instead of hiring a team of experts to monitor and troubleshoot network issues, AI-driven tools have the capabilities to analyse massive amounts of data to help IT teams judge and approve network decisions with precision and confidence. With networks operating more efficiently, fewer resources are needed. AI simplifies network management by actually understanding the business intent, thanks to recent AI integrations that include business intent cognition.
AI-powered digital twins
Another aspect of AI-powered NaaS is digital twin technology, which creates a virtual model of an enterprise network. This technology can simulate numerous network changes and identify the most efficient configurations before implementation. However, AI is not flawless; challenges persist, especially when interacting with Generative AI (GenAI) technologies. Ultimately, NaaS AI solutions still require human oversight and judgment. While no AI can replace human decision-making, ongoing training may improve AI’s accuracy, reducing the business demand for IT expertise.
Looking at current networking management, there are two types of AI that can be used to monitor and analyse network actions. They are:
- GenAI – which processes huge amounts of data to answer human queries in natural language, offering a transparent interface and intuitive recommendations for human operators.
- AI-driven remote monitoring and management (RMM) – which builds a deep understanding of the network and is able to forecast potential disruptions based on trends and patterns.
Optimising insights from both of the approaches – human- initiated and AI-initiated – enterprises are able to better manage their networks, and IT teams, making them more resilient and efficient.
Trusting AI in network management
We emphasised earlier that AI in networking management still requires time and trust. It is understandable that businesses remain cautious and doubtful about giving full control to an AI-driven system. Looking at the bigger picture, enterprises choose NaaS agreements wholly because they want to avoid spending energy, time or money on understanding network operations. In any form of business, people are hired based on their competency to the get the job done – and AI in NaaS delivers just that.
Ultimately, businesses want assurance that their networks can function reliably. The same applies to any type of enterprise, regardless the size of the business. The addition of AI management to the NaaS model makes it a much more reasonable option across all these scenarios.
The future of AI and NaaS
This year, we will see a turning point for NaaS, as AI becomes more integrated into network management. This will ease the challenges faced by IT teams and relieve businesses looking for highly skilled and costly IT professionals. Enterprises that adopt AI-powered NaaS will reap the benefits through proactive RMM troubleshooting and advanced digital twin modelling. With the help of advanced AI toolkits, IT teams will have the opportunity to do, learn and develop more on the job.
NaaS and AI combined represents the future of enterprise networking. Those who embrace this shift will be well-positioned for success in the fluid digital landscape. For those described here, it’s safe to say that we can believe the hype around the future of NaaS and AI.
