WBA publishes initial guidance on artificial intelligence, machine learning for intelligent Wi-Fi

The Wireless Broadband Alliance (WBA) has published a report outlining an industry-wide perspective for device manufacturers, network operators, enterprise IT and policymakers on how artificial intelligence (AI) and machine learning (ML) can be integrated across the full Wi-Fi ecosystem.

The AI/ML for Wi-Fi: Enabling scalable, intelligent Wi-Fi ecosystems report was developed by the WBA AI/ML for Wi-Fi Project Group, and led by Intel with Airties, Cisco and HPE.

The founding viewpoint from the WBA is that traditional rule‑based management approaches for Wi‑Fi technology are no longer adequate as they are now asked to support increasingly support demanding applications such as enterprise collaboration, industrial automation, immersive media and AI workloads. The report outlines business benefits including lower operational costs, stronger reliability and security, and an improved user experience.

The report shows how AI and ML are becoming foundational to Wi-Fi, enabling a shift from reactive troubleshooting to predictive, proactive and self-optimising network operations capable of managing dense deployments and real-time performance demands.

In addition, it highlights how 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). Moreover, the report argues that AI will not just sit at the router: instead, it will combine client, access point, edge and cloud intelligence to achieve the best performance.

However, it also observed that data is the primary bottleneck, and that achieving continued success and new use cases with AI/ML in networks requires shared datasets, federated learning and strong governance models. Fragmentation also remains a major barrier.

Going forward, WBA advises that standardisation should focus on frameworks and not algorithms. It added that interoperability will need to include data models, telemetry, application programming interfaces and model lifecycle management. WBA also believes that AI/ML-native Wi-Fi is the long-term technological direction and that features of Wi-Fi 8 (IEEE 802.11bn), such DBE and MAPC, will work optimally when driven by an AI/ML engine.

Commenting on the report, Tiago Rodrigues, Wireless Broadband Alliance president and CEO, said: “Wi-Fi is now expected to perform like critical infrastructure across homes, enterprises and cities, yet operational complexity is rising fast. 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.”

Matthew MacPherson, wireless chief technology officer at Cisco, added: “As Wi-Fi becomes the primary connectivity technology for mission-critical enterprise applications, the complexity of managing these environments has outpaced traditional manual methods.

“This report provides a vital framework for the industry to transition from reactive troubleshooting to a proactive, self-optimising architecture,” he said. “By leveraging AI and machine learning through interoperable standards, we are enabling organisations to reduce operational overheads and deliver a more resilient, high-quality experience for every user and device.”

Eric McLaughlin, vice-president and general manager of Intel, said: “AI/ML is transforming the future of Wi-Fi, and it has become a strategic imperative. We are excited to collaborate with our WBA partners and the broader ecosystem to accelerate its advancement to enable self-organising, proactive, and more reliable networks with improved QoE across the industry.”