WBA publishes guidance on AI and ML for intelligent Wi-Fi

According to the Wireless Broadband Alliance (WBA), as Wi-Fi networks become more complex and mission-critical, traditional rule-based management approaches are no longer sufficient for network operations. The WBA’s latest report, ‘AI/ML for Wi-Fi: Enabling Scalable, Intelligent Wi-Fi Ecosystems’, highlights how AI/ML enables a shift from reactive troubleshooting to predictive, proactive and self-optimising network operations. The WBA says the report also outlines clear business benefits including lower operational costs, stronger reliability and security, and an improved end‑user experience.

As Wi‑Fi technology grows more complex and becomes mission‑critical — supporting increasingly demanding applications such as enterprise collaboration, industrial automation, immersive media and AI workloads — traditional rule‑based management approaches are no longer adequate.

The report provides an industry-wide perspective for device manufacturers, network operators, enterprise IT and policymakers, on how AI/ML is being integrated across the full Wi-Fi ecosystem.

Artificial intelligence and machine learning are becoming foundational to Wi-Fi

Bringing together industry analysis, real-world use cases and ongoing standardisation efforts, the report presents a unified perspective on intelligent Wi-Fi. Key findings from the report include:

• AI/ML is becoming foundational to Wi-Fi: It is critical for enabling autonomous, self-optimising networks capable of managing dense deployments and real-time performance demands.
• Intelligent Wi-Fi has clear business value: AI/ML reduces operational costs (OpEx), improves reliability and security and delivers a more consistent quality of experience (QoE).
• Fragmentation remains a major barrier: Proprietary approaches, inconsistent data quality and closed interfaces slow innovation and increase integration costs.
• Standardisation should focus on frameworks: Interoperable frameworks, not algorithms, will be key to success. That interoperability will need to include data models, telemetry, APIs and model lifecycle management.
• Hybrid AI architectures will dominate: AI will not just sit at the router, it will combine client, access point, edge and cloud intelligence to achieve the best performance.
• AI/ML-native Wi-Fi is the long-term direction: Features of Wi-Fi 8 (IEEE 802.11bn), such as DBE and MAPC, will work optimally when driven by an AI/ML engine.
• Data is the primary bottleneck: Achieving continued success and new use cases with AI/ML in networks requires shared datasets, federated learning and strong governance models.
   

Developed by the WBA AI/ML for Wi-Fi Project Group, the work was led by Intel and co-led by Airties, Cisco and HPE. The WBA will share the findings with industry stakeholders and standards bodies, including Wi-Fi Alliance and IEEE 802.11 meetings in March 2026.

“Wi-Fi is now expected to perform like critical infrastructure across homes, enterprises and cities, yet operational complexity is rising fast,” said Tiago Rodrigues, President and CEO of the WBA. “AI and machine learning are becoming essential to keep networks reliable, secure and efficient at scale. The industry must align on common data, interfaces and governance, so that intelligent Wi-Fi can work across real-world multi-vendor environments and deliver value for all who use it.”

“As Wi-Fi becomes the primary connectivity technology for mission-critical enterprise applications, the complexity of managing these environments has outpaced traditional manual methods,” said Matthew MacPherson, Wireless CTO, Cisco. “This report provides a vital framework for the industry to transition from reactive troubleshooting to a proactive, self-optimising architecture. By leveraging AI and machine learning through interoperable standards, we are enabling organisations to reduce operational overhead and deliver a more resilient, high-quality experience for every user and device.”

The ‘AI/ML for Wi-Fi: Enabling Scalable, Intelligent Wi-Fi Ecosystems’ report is available for download at https://wballiance.com/ai-ml-for-wi-fi-report/.

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