- Boldyn Networks executive Andrew McGrath says the growth of AI will significantly increase demand for network capacity and edge connectivity.
- Neutral-host infrastructure and distributed networks may play a larger role as traffic patterns shift.
What Happened
Artificial Intelligence could become a major driver of telecom infrastructure demand, according to comments from Andrew McGrath of Boldyn Networks. In a recent discussion about industry trends, McGrath argued that AI workloads are likely to reshape the way operators plan and deploy networks.
McGrath said the growth of AI applications—from generative models to automated systems—will generate new volumes of data traffic. These systems rely on constant data movement between devices, edge nodes, and cloud platforms. That shift could place pressure on network capacity, particularly in dense urban environments and large venues.
Boldyn Networks focuses on neutral-host connectivity infrastructure, including fibre, distributed antenna systems, and private wireless networks. McGrath suggested such shared infrastructure could help meet growing connectivity demands in locations like stadiums, transport hubs, and smart city deployments.
The discussion also highlighted how enterprises are increasingly adopting private networks and edge computing. These technologies allow companies to process data closer to users or devices. In theory, this can reduce latency for AI-driven applications such as automation or real-time analytics.
However, McGrath cautioned that scaling AI connectivity will require continued investment in fibre backhaul, wireless infrastructure, and edge capacity. The telecom sector must prepare for higher traffic loads and different traffic patterns as AI workloads expand.
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Why It’s Important
The idea that AI will reshape telecom networks is gaining traction across the industry. AI systems rely heavily on fast data exchange between compute clusters, cloud services, and connected devices. This creates demand not only for computing power but also for robust connectivity.
Telecom operators may see opportunities in this shift. New traffic flows could drive demand for fiber networks, edge infrastructure, and advanced wireless systems such as 5G and private networks. Vendors and infrastructure providers are already positioning themselves to support these workloads.
Yet the business case remains uncertain. Many operators are still working to monetize 5G investments, and large-scale AI adoption may not immediately translate into telecom revenue. Much of the value in AI ecosystems currently accrues to cloud providers and software companies rather than network operators.
There are also technical challenges. AI traffic patterns can be unpredictable and highly concentrated around data centers and training clusters. Networks built primarily for consumer broadband may require redesign to handle these workloads efficiently.
McGrath’s comments underline a broader debate in telecoms: whether AI will create a new growth cycle for connectivity providers or simply increase network costs without guaranteeing stronger returns.
