New research shows that AI is about to put enterprise networks under intense pressure. Globally, network traffic will triple in just three years as agentic AI expands. And in two years, most enterprises expect they’ll hit the limits of their campus and branch network capacity. At the same time, attack surfaces are already growing faster than defenses can keep up.
This research, released by Cisco in partnership with Foundry, confirms that large language models (LLMs) and the emerging wave of agentic AI are straining enterprise campus and branch networks more than ever. Alongside compute, the network is now a critical factor in whether enterprise AI deployments succeed or fail.
AI will triple network traffic in three years
A third of the global organizations surveyed already have broad, enterprise-wide agentic AI deployments. In India, 99% of organizations expect agentic AI use to grow within 24 months. Mature AI adopters globally also expect AI-driven traffic to more than triple over the next three years, a 235% jump.
That surge comes from how agentic AI works. Unlike human users, AI agents operate at machine speed, triggering dozens of API calls, database lookups, and model inferences in seconds.
They generate dense east-west traffic, lateral communication between devices or servers that AI agents need to exchange data. Legacy workplace networks were never designed to handle this kind of workload.
On the generative AI side, traffic is mostly north-south. On the agentic AI side, it’s mostly east-west. Networks are usually built for predictable traffic patterns, but now three agents might be trying to talk to each other to solve a problem. The question is how to support that increase in east-west traffic, said a Head of AI Strategy from a US tech firm interviewed for the research.
These agentic AI workloads, which can transform enterprises, are also uniquely fragile. Networking leaders in India say AI workloads are acutely vulnerable to network issues, more sensitive than traditional applications to reliability and uptime (84%), bandwidth (80%), latency (75%), and packet loss (63%).
Network capacity will hit its limit in two years
Fewer than one-third of mature AI adopters globally say their networks are fully prepared for projected AI growth. In India, 71% of respondents admit they need upgrades, and 75% say they have already hit, or will hit, campus and branch capacity limits within 24 months.
Wi-Fi is emerging as a major bottleneck for AI, with more than half of global respondents saying it’s driving the biggest increase in capacity requirements.
There’s still a gap between ambition and reality. Three-quarters of global IT leaders say they’re more confident in their organization’s AI strategy than in the network’s ability to deliver it. While 92% of Indian respondents cite budget constraints as a barrier, almost all enterprises are planning to modernize their workplace networks.
Attack surfaces are expanding while observability falls short
AI has also created a tougher security environment. The vast majority of Indian organizations say they’re struggling to keep up (97%) and that AI has already caused some damage (93%).
Over two-thirds of global respondents believe AI-related threats are evolving faster than their ability to adapt, and that failing to upgrade networks over the next two years will only increase security risks. Meanwhile, an observability gap is widening as traditional monitoring tools struggle with bursty, east-west agentic traffic flows.
We’re just playing catch-up right now. It’s a worrying time, and I think it’ll stay like this for another 18 months to two years, said a VP of IT and Digital Infrastructure in education in the UK.
Modernization is no longer optional
These findings make one thing clear that network resilience, observability, and adaptive security are not optional in the AI era. They’re essential.
The network has survived decades of transformation, from the dot-com boom to cloud adoption, by adapting to meet each new challenge.
Organizations that treat network modernization as a prerequisite for their AI strategy, rather than a side project, will define the next decade of enterprise AI.
Methodology
Foundry conducted a quantitative survey, co-designed and sponsored by Cisco, of 3,472 CIOs as well as networking, end user computing, and technology leaders in Asia-Pacific, Europe, the Middle East, Latin America, and North America.
The respondents work at organizations with 500+ employees that have an average of 3,292 campus/branch locations.
In addition, Foundry conducted six in-depth interviews with executives in Asia-Pacific, Europe, and the United States. All research was conducted between March and April 2026.
*All views expressed in this article belongs exclusively to CISCO Research and do not reflect the views of The Volt Post. The Volt Post is not responsible for the opinions, figures, or statistics presented here.
