AI Is Driving More Network Inspection. Can Your Security Keep Up?

Generative AI has quickly moved from experimentation to everyday business use. Employees use AI tools to create content, write code, analyze data, automate repetitive tasks, and interact with business applications in entirely new ways. At the same time, software vendors are embedding AI capabilities into the products organizations already use every day, often without requiring users to adopt separate tools.

This rapid adoption is creating a challenge that receives far less attention than AI's impact on productivity or infrastructure costs: the growing need for network inspection.

As AI becomes part of everyday workflows, organizations are sending more data to cloud services, interacting with more applications, and generating larger volumes of encrypted traffic. According to Netskope, the amount of data sent to generative AI applications increased more than 30-fold in a single year, highlighting how quickly AI has become embedded in modern business operations.

For security teams, this trend creates a visibility problem.

Most modern applications rely on encrypted communications to protect privacy and sensitive information. While encryption is essential, it also reduces visibility into what is happening across the network. Security teams must work harder to identify threats, enforce policies, understand application usage, and maintain consistent protection across users, devices, and locations.

The rise of AI amplifies this challenge. Employees routinely upload documents, submit business information via prompts, connect applications to external services, and interact with cloud-based AI platforms throughout the day. As AI usage expands, organizations need greater visibility into network activity, not less.

At the same time, the underlying nature of network traffic is beginning to change. Cisco research found that AI traffic behaves differently from traditional web traffic and is growing rapidly. AI inference connections tend to remain active longer and create different network demands than conventional applications. Researchers also observed AI traffic increasing fourfold over just eight months across the monitored networks. Cisco’s infographic.

This shift is increasing the importance of traffic inspection.

Historically, organizations primarily evaluated network infrastructure based on throughput. Today, the more important question is whether security platforms can continue to inspect traffic effectively when advanced security services are enabled, and traffic volumes continue to grow. Inspection requirements now extend well beyond basic threat prevention. Organizations need visibility into applications, encrypted communications, user activity, and potential risks as they move across the network.

If security infrastructure cannot keep pace, performance can suffer. Latency increases, user experience degrades, and IT teams may face pressure to reduce inspection or disable security services to maintain responsiveness. When that happens, security becomes a bottleneck rather than a business enabler.

This is why modern firewalls continue to play a critical role in AI-driven environments.

As AI adoption accelerates, organizations need more than raw bandwidth. They need platforms capable of inspecting encrypted traffic, enforcing security policies, maintaining application visibility, and supporting advanced security services without compromising performance. Firewalls remain one of the most strategic control points in the network because they sit directly in the path of the traffic organizations must understand and secure.

High-capacity environments place even greater demands on these controls. Campuses, distributed enterprises, data centers, and service-provider networks must support growing traffic volumes while preserving visibility and maintaining security effectiveness.

To address these requirements, WatchGuard introduced the High-Performance Firebox Series. These rack-mount appliances are designed for organizations that require scalable performance and resilient security infrastructure, offering native 25G and 100G connectivity, 100G expansion through OCP 3.0, redundant power supplies, and hot-swappable fans. More importantly, they are built for environments where inspection, security services, and high-speed connectivity must operate simultaneously without creating operational bottlenecks.

The growth of AI is not simply creating more traffic. It is creating more traffic that organizations must inspect, understand, and secure. As encrypted communications continue to grow and AI applications become a normal part of business operations, maintaining visibility at scale will become a key requirement for security teams and MSPs alike.

Organizations that prepare for this shift today will be better positioned to support future AI initiatives while maintaining performance, resilience, and protection. In the AI era, the ability to inspect at scale may become just as important as the ability to connect at scale.

Learn more about WatchGuard's AI strategy:
https://www.watchguard.com/wgrd-platform/rai