One interesting point about VPNs is raised by fully a third of capacity-hungry enterprises: SD-WAN is the cheapest and easiest way to increase capacity to remote sites. Yes, service reliability of broadband Internet access for these sites is highly variable, so enterprises say they need to pilot test in a target area to determine whether even business-broadband Internet is reliable enough, but if it is, high capacity is both available and cheap.
Clearly data center networking is taking the prime position in enterprise network planning, even without any contribution from AI. Will AI contribute? Enterprises generally believe that self-hosted AI will indeed require more network bandwidth, but again think this will be largely confined to the data center. AI, they say, has a broader and less predictable appetite for data, and business applications involving the data that’s subject to governance, or that’s already data-center hosted, are likely to be hosted proximate to the data. That was true for traditional software, and it’s likely just as true for AI.
Yes, but…today, three times as many enterprises say that they’d use AI needs simply to boost justification for capacity expansion as think they currently need it. AI hype has entered, and perhaps even dominates, capital network project justifications.
These capacity trends don’t impact enterprises alone, they also reshape the equipment space. Only 9% of enterprises say they have invested in white-box devices to build capacity and data center configuration flexibility, but the number that say they would evaluate them in 2026 is double that. This may be what’s behind Cisco’s decision to push its new G300 chip. AI’s role in capital project justifications may also be why Cisco positions the G300 so aggressively as an AI facilitator. Make no mistake, though; this is really all about capacity and QoE, even for AI.
