"AI and ML are critical for enabling autonomous, self-optimizing Wi-Fi networks capable of managing dense deployments and real-time performance demands. AI/ML reduces operational costs, improves reliability and security and delivers a more consistent quality of experience. Proprietary approaches, inconsistent data quality, and closed interfaces slow innovation and increase integration costs. Interoperable frameworks - not algorithms - will be key to success. Interoperability must include data models, telemetry, APIs, and model lifecycle management."
"AI will not just sit at the router. It will combine client, access point, edge and cloud intelligence to achieve the best performance. Features of Wi-Fi 8 (IEEE 802.11bn), such dynamic bandwidth expansion (DBE) and multi-access point coordination (MAPC), will work optimally when driven by an AI/ML engine. Achieving continued success and new use cases with AI/ML in networks requires shared datasets, federated learning and strong governance model."
Wi‑Fi networks have become mission‑critical across homes, enterprises and cities while operational complexity is rising. AI and ML must replace rule‑based management to enable predictive, proactive, and self‑optimizing network operations that handle dense deployments and real‑time performance demands. Successful AI/ML evolution lowers operational costs, strengthens reliability and security, and improves end‑user experience. Proprietary solutions, inconsistent data quality, and closed interfaces hinder innovation and increase integration costs. Interoperable frameworks — covering data models, telemetry, APIs, and model lifecycle management — are essential. AI intelligence will span client, access point, edge, and cloud. Shared datasets, federated learning, and strong governance enable continued success and new use cases.
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