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You are here: Home / Videos / Resilient Wireless Networks for AI with Cisco Enterprise Networking

Resilient Wireless Networks for AI with Cisco Enterprise Networking



AI Infrastructure Field Day 4


This video is part of the appearance, “Cisco Enterprise Networking Presents at AI Infrastructure Field Day“. It was recorded as part of AI Infrastructure Field Day 4 at 10:30AM - 12:30PM PT on January 28, 2026.


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Minse Kim, Cisco’s wireless product manager, emphasized that the AI era is profoundly changing enterprise networking, extending beyond data centers to encompass “physical AI” applications in factories, medical facilities, and dynamic workspaces. He noted that surging demand for AI infrastructure components is also influencing customer buying cycles, with some customers proactively investing in Wi-Fi 7 now. A key insight is that while AI infrastructure is often perceived as data center-centric, the actual consumption and training of AI models, particularly for robotics and autonomous systems, relies heavily on high-performance, low-latency wireless connectivity, making Wi-Fi 6, 6E, and 7 crucial “last mile” technologies. Cisco’s Wi-Fi 7 access points are designed to meet these demands, offering multi-gigabit speeds and backhaul capabilities up to 20 Gbps per AP.

Addressing Wi-Fi’s traditional reliability-versus-speed trade-off, Cisco has developed Ultra-Reliable Wireless Backhaul (URWB) capabilities integrated into its Wi-Fi 7 APs. By dedicating a radio, URWB provides a stable, predictable, and low-latency “wired-like” connection, which is essential for critical applications like robotics that cannot tolerate the blips and jitters common in traditional Wi-Fi during client roaming. Beyond connectivity, Cisco Wi-Fi 7 APs also enhance spatial awareness and location services. Leveraging technologies such as 802.11mc (FTM) and Ultra-Wideband (UWB) with sensor fusion, these APs deliver sub-meter (e.g., one-foot) location accuracy and low latency, resolving long-standing problems in asset tracking and network operations, as demonstrated by real-time asset tracking in an office environment. This ability to accurately digitize the physical world is fundamental for AI analytics.

Furthermore, Cisco is integrating AI into network operations to simplify management and optimize performance. For instance, AI models leverage telemetry data from 35 million Cisco APs globally to intelligently manage firmware upgrades, learning from customer rollback decisions to improve future deployments. AI also enhances Radio Resource Management (RRM) by moving beyond simple rule-based engines to intelligently optimize RF configurations, leveraging historical interference patterns and dynamically adapting to environmental changes to maximize network efficiency and stability. Cisco is even introducing the concept of APs acting as “synthetic clients” to proactively collect network statistics and provide informed recommendations. This comprehensive AI-powered approach, delivering ultra-reliable, high-speed wireless, precise spatial awareness, and intelligent network automation, is not a future vision but a current reality, with thousands of customers already using Cisco’s AI-powered network solutions.

Personnel: Minse Kim

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