AI, Fibre, Wi-Fi and Network Convergence

AI deployment across fixed and wireless networks is accelerating, with tier-one operators like Deutsche Telecom, BT, AT&T, Verizon, Orange, and Vodafone leading the charge. These implementations focus primarily on:

• Network planning and supply chain optimization - delivering measurable efficiency benefits
• Predictive maintenance - identifying potential network breakpoints before they occur
• Energy consumption management - meeting regulatory requirements through AI-powered solutions
• Enhanced security measures - leveraging AI to protect network infrastructure
• Quality of Service (QoS) and Quality of Experience (QoE) - using AI to collect and analyze data for improved user experiences

As Craig Thomas explains: "From my side, I think it's very important to define what we mean by AI. First of all, you know, are we talking about Gen AI, AI Agents versus Agentic AI, network planning and analytical AI, etc. They're slightly different things. You show me a tier one that hasn't deployed AI to a certain degree already."

Tiago Rodrigues highlights practical applications in wireless networks: "In the wireless brand space, we have been seeing a lot of AI developments, particularly looking into quality of service and quality of experience. That has been an area that provides a lot of insights and information that can improve the experience to the end user device."

Beyond network operations, AI is enabling entirely new service categories through technologies like Wi-Fi sensing. This innovative approach transforms standard Wi-Fi routers into multi-purpose devices capable of:

• Home security applications - detecting intrusions and unusual activity
• Healthcare monitoring - including fall detection and even breathing/heart rate monitoring
• Smart home automation - enhancing everyday living experiences

Marc Einstein describes this exciting development: "At Network X in Dallas, I was on a panel talking about Wi-Fi sensing. And so, you know, we have everything in the network itself, deployment and operations and customer service and all that. But now we're actually just starting to see things being built on top... your Wi-Fi router is actually about to now have applications in the home security market and it's about to have applications in the healthcare market."

Similar to Wi-Fi sensing but deployed in outside environments, fibre sensing represents an emerging opportunity for network operators. This technology utilizes existing fibre infrastructure to detect environmental changes with AI-powered analytics interpreting sensor data.

Craig Thomas elaborates on this emerging technology: "Looking outside the home as well, AI working with fibre sensing to looking at things like disaster measurement and traffic control and infrastructure checks, etc., there's fibre sensing outside opportunities as well as that Wi-Fi sensing in the home that all has an AI role."

He further explains: "The fibre is going to be everywhere. It can measure if there is a tremor in the ground or if it's going over a bridge, etc. So, this is third-party parallel industries that the fibre networks can help with."

The evolution toward autonomous networking represents a significant shift in how networks operate. Agentic AI—systems capable of making independent decisions—is becoming essential for:

• Automatic Wi-Fi optimization within homes without human intervention
• Dynamic network path selection to maintain application-specific QoE requirements
• Real-time traffic management across diverse network conditions

On the critical role of autonomous AI systems, Craig Thomas states: "If you're going to have the full benefits of AI, the agentic AI is critical, so it can make its own decisions autonomously, so that if there's something wrong with the Wi-Fi, for example inside the home, it can make those changes there and then without actually having a third party human interface."

Irrespective of your AI Strategy. Roadmap and End-Goal, any AI is only going to be as good as the “Big Data” you collect to model your AI strategy around. Simply speaking get your data collection and data lakes right before implementing any widespread AI strategy, whether that is internal data sheared across business groups or wider external collective data lakes.

The industry continues to work toward meaningful convergence between fixed, mobile, and satellite networks, though significant challenges remain. Current convergence efforts focus on:

• Service-level convergence - such as Wi-Fi calling that leverages fixed broadband for mobile experiences
• Authentication convergence - using SIM credentials across network types
• Core network integration - developing common service management and orchestration through technologies like Access Gateway Function (AGF)
• Unified customer premises equipment (CPE) - creating common device stacks regardless of connection type

Tiago Rodrigues frames the convergence challenge: "On the convergence maybe it's important that we start to frame what means convergence. So, there is different layers related to that... We have for example how to authenticate on Wi-Fi using the SIM card and that's another somehow convergence component. Then there is a lot of discussion, but I think it's still a few years ahead of us to bring the convergence discussion to the networks."

Craig Thomas adds perspective on the market shift: "For the previous 5-10 years, all the investment was being made in the 5G or the 4G network before that. Where we're seeing a slight shift where there is renewed investment in the fixed and in the fixed Wi-Fi network. So that brings up the convergence discussion even more."