AI-Supercharged NaaS Will Help Solve Enterprise IT Staffing Challenges in 2025

One place where we are seeing a real AI-powered revolution is in network as a service (NaaS) deployments in enterprise networks. Much more than just another feature, AI is actually changing the calculus on the benefits of the NaaS model and, we believe, will drive broader and deeper NaaS implementations across a number of enterprise verticals as its advantages become better known in 2025.

The NaaS service model

NaaS is essentially a third party-provided network in a box. It’s a cloud-based service model that enterprises use, on a contract basis, to drive their own network infrastructure. In the NaaS model, the provider monitors, manages and optimizes the enterprise’s network via software over the internet, potentially replacing on-premise hardware as well. Even more than that, however, NaaS represents a philosophical shift from network-first thinking to a deeper focus on end-user experience. SLAs assume even stronger significance in NaaS because the enterprise’s only meaningful metric is that user experience.

This business model is economical compared to maintaining a large, in-house IT department and network hardware and it is secure because the provider integrates security services into the network. It’s flexible and scalable because network reconfigurations can all be done remotely via software, and adding capacity is as simple as adjusting the service plan. All these benefits add up to a powerful value proposition: NaaS frees up an enterprise to focus on its own business.

Yet, in spite of all these advantages, NaaS adoption remains relatively lukewarm due to inertia and a perceived lack of a useful toolkit to gain insights, and inability to exercise simplified and granular control of the network with a lean, economical IT team. It’s never really been a hands-off, turnkey solution; specialized IT expertise is still required, and that expertise is getting harder to find and afford. This reluctance is changing, however, and ABI Research now estimates that more than 90% of enterprises will incorporate some degree of NaaS networking by the year 2030.¹

AI is the NaaS change maker

AI delivers that missing NaaS toolkit, presenting a genuine game changer for enterprises. Current and imminent AI integrations are poised to take NaaS capability, utility, efficiency and economy to the next level by overcoming these persistent limitations—and it all starts with understanding the enterprise’s chief concerns.

First, AI integration goes a long way toward creating an evolving, future-ready NaaS deployment, assuring enterprises that the inevitable upgrade cycles are already baked into the cake. Today, enterprises are dealing with more advanced technology managed by fewer people; stricter SLAs and more dire consequences for network disruptions; and the cost and scarcity of IT expertise. These factors increase cost and risk in doing business, with little or no direct benefit to the enterprise’s actual product.

The common denominator in these concerns is staffing. With fewer resources to put toward IT headcount, enterprises can find themselves bogged down in network complexity due to multiple layered technologies including Wi-Fi®, private cellular, Zigbee®, Bluetooth®, PON, Matter and others. Each of these services connect a dizzying array of devices and applications, creating a cluttered family tree of interdependent technologies that even the most seasoned IT expert can’t unravel—even if such an expert was readily available.

Enter AI-powered NaaS. The AI integrations now coming online for 2025 feature natural language AI interfaces that can help IT understand, judge and approve network decisions with unprecedented confidence and clarity. Even junior IT staff can deliver Ph.D. results if guided by Ph.D.-level AI. Indeed, the latest AI network integrations include business intent cognition, which enables the AI to actually understand the intent behind the business itself—and use that understanding to creatively formulate business requirements and policies into the network that support the business intent.

Creative thinking, proactive management

AI-powered NaaS also drives digital twins, a network design model that simulates countless network changes, seeking efficiencies that would escape a human architect. That said, it is still true that AI isn’t a perfect solution right out of the box. The quirks known to pop up in generative AI interactions are still a real thing; while the technology is always improving, NaaS AI solutions must remain, ultimately, subject to human control and judgment. In its current state, no AI can replace a human decision chain. However, with time and training, the AI improves its accuracy and utility as a tool, reducing pressure on the enterprise to resource for the most advanced IT expertise.

When it comes to ongoing network management, AI can employ two general types of intelligence to monitor, analyze and recommend network actions. They are:

• Generative AI (GenAI), which uses amassed data to respond to human queries in natural language. This interface is transparent and GenAI likewise gives its recommendations in intuitive language to the human operator.
• AI-driven remote monitoring and management (RMM), which is less transparent but more proactive in offering recommendations. RMM builds a deep understanding of network parameters and seeks out potential problems before they manifest.

The insights provided from these two approaches—human-initiated and AI-initiated—are what makes it possible for a limited IT team to stay ahead of network challenges.

Building trust, building on precedent

As mentioned earlier, learning to trust the insights and recommendations of AI in a NaaS environment takes time and effort, both in how humans ask questions and how the AI expresses advice. Of course, establishing trust is as important as establishing trust with a critical employee, because in many ways, that’s pretty much what the function of NaaS AI is. Enterprises hire people who can get the job done without complicating matters for others; in terms of NaaS, it’s a matter of meeting SLAs, not explaining the specs. Enterprises engage NaaS agreements precisely because they don’t want to waste energy, time or money on figuring out how the network operates. They just want to know with the highest certainty that it does. And this is true no matter what kind of enterprise we’re looking it, from a medium-sized business to a school district, stadium, multi-dwelling unit, hospital or airport—and the addition of AI management to the NaaS model makes it a more practical option for all these scenarios.

AI is here. Will your network benefit?

2025 will be the year NaaS is supercharged by novel AI capabilities, which will relieve the stress of IT cost and availability, while also simplifying the learning curve for IT staff. The opportunities for efficiency are many, from proactive RMM troubleshooting to advance digital twin modeling, and IT teams will be able to do more—and learn more on the job—with the assistance of advanced AI toolkits.

Together, NaaS and AI are more than a combined technology; they become the cornerstone of success in the digital age. We can believe the hype around the future of NaaS and AI. 

¹ABI Research (January 2023) 90% of Enterprises will Adopt Network-as-a-Service by 2030, But Uncertainty Keeps Market Nascent. https://www.abiresearch.com/press/90-of-enterprises-will-adopt-network-as-a-service-by-2030-but-uncertainty-keeps-market-nascent/

This article was first published in The Fast Mode.

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