New research from Cisco and Foundry finds that, three years from now, AI will triple network traffic. In two years, most enterprises will hit campus and branch network capacity limits. And globally, attack surfaces are already expanding beyond what defenses can manage.
The report, "No time to wait: The accelerating impact of AI on campus and branch networks" confirms that, alongside compute, the network is now a major factor in whether enterprise AI deployments succeed or fail.
Download the reportHow is AI affecting your network?
3 years from now traffic triples as Agentic AI expands
0%
expect moderate or major expansion in agentic AI deployment in the next 24 months.
0%
already have broad enterprise-wide deployment of agents.
AI is already reshaping traffic patterns, driving increases that traditional networks were not designed to support.
0%
are already seeing increases in east-west traffic.
0%
have seen an increase in latency-sensitive traffic.
0%
report increases in continuous automated system traffic.
0%
told us they are seeing increases in bursty/spike-driven traffic.
The same AI workloads that have the potential to transform enterprises are also uniquely fragile. Compared to traditional enterprise apps, mature AI adopters say their AI workloads are far more sensitive to:
Reliability and uptime
Bandwidth
Latency
Packet loss
In 2 years network capacity reaches its limit
0%
say AI has already created network problems.
0%
say they have hit or expect to hit campus and branch network capacity limits within the next 24 months.
Infrastructure is outdated
- 76% of respondents admit their network needs upgrades.
- Organization are reacting: AI has accelerated modernization plans for 93% of organizations.
- But only 30% of aggressive AI adopters report being fully prepared to support projected AI growth across the network.
Wi-Fi is being hit the hardest
AI-driven demand has caused the greatest increase in performance and capacity requirements in:
- Campus Wi-Fi50%
- Data centers37%
- WAN traffic37%
- Branch locations31%
Time is running out
- 34% increase reported in network traffic already as a result of AI.
- Companies broadly deploying AI expect total network traffic to triple in the next three years.
- Yet 75% say their organizations are more confident in their AI strategy than in the network's ability to deliver it.
- Capacity planning built for a 5-year horizon is colliding with a 24-month reality.
Pressure points
The strain on networks is evident everywhere we look…
AI’s front-runners are hitting a wall
- The number of Pacesetters, organizations outperforming their peers on AI, has declined since 2023.
- 41% of Pacesetters say their existing infrastructure, specifically dated networks, cannot support AI deployments at scale.
AI Readiness Index 2025
8,039 senior business leaders responsible for AI integration and deployment in large organizations across 30 markets.
Wireless leaders are struggling with complexity
- 81% of wireless leaders want AI to simplify operations, but only 26% have achieved high level implementation.
- Wireless leaders in organizations deploying AI are more likely to have to solve congestion issues (72% vs. 46%) and enable high- bandwidth applications (70% vs. 32%).
State of Wireless 2026
6,098 wireless decision makers and technical specialists in 30 markets.
AI-related outages are universal, visibility isn't
- Every technology leader surveyed admitted their organization has experienced some form of AI-related downtime.
- Observability remains a challenge with 47% of technology leaders admitting that customers are often the first to detect downtime.
Splunk’s Hidden Costs of Downtime 2026
2,000 executives from Global 2000 companies in 20 countries.
Agentic inference risks overloading the WAN
- Up to 450% more total traffic is generated per task when performed by an agent.
- Approximately 70% of that traffic is AI inference, making inference paths mission-critical.
AI Impact on Wide Area Networks 2026
Direct measurement of live AI inference traffic across service provider networks.
Attack surfaces are already expanding
There is widespread agreement that AI is increasing security risks.
77% have already found that AI has increased their attack surface over the last year.
And 72% say that not updating networks in next 12-24 months will result in increased risks.
The struggle to keep up
86%
say their organizations have already added security controls to support AI workloads.
72%
agree that AI related security threats are evolving faster than their ability to adapt.
Observability gaps are widening
69%
believe that AI workloads have introduced new blind spots in network security monitoring.
59%
say they lack adequate visibility into AI-related traffic flows across the network.
Current postures and policies may not be enough
68%
say the distributed nature of AI workloads makes it harder to maintain consistent security policies.
65%
agree that their current campus and branch posture may not be sufficient for next-gen AI workloads.
Industry leaders react
Through a mix of interviews and industry-wide insights, AI industry leaders reveal how AI is impacting their campus and branch networks.
Modernization is a must
The network has survived decades of transformation, from dot-com to the cloud, by adapting and evolving to meet the moment. And it will do so again. But it won’t happen without decisive, immediate action. Agentic AI is arriving at a moment when most networks are underprepared, under-observed, and underfunded. The companies that are recognizing this earliest, and adapting fastest, will define the next decade of enterprise AI. The ones that don't, risk spending the next ten years troubleshooting.
