AT&T’s GenAI Strategy? Plug It In Everywhere

• AT&T has a strategy for its network to operate autonomously, with minimal human intervention
• The telecom giant is integrating GenAI into more and more aspects of the network lifecycle, including the retirement of copper
• But AT&T is implementing GenAI strategically and in parallel with other network transformation activities.

From the early stages of development to the final stages of decommissioning, artificial intelligence (AI) is slowly creeping into every corner of AT&T’s network lifecycle. The telecom giant’s work with generative AI (GenAI) extends far beyond the chatbots that carriers are known for. Raj Savoor, AT&T’s vice president of network analytics and automation, told Fierce that the company is now using the technology to aid in the copper retirement effort.

“We leverage both open source data and commercial GenAI engines to streamline these processes,” Enjoy Traditionally, dismantling infrastructure involved sending a technician to assess and document each site. Today, much of this work can be done remotely using public domain visual analytics data and AI-powered support systems.

The amount of manual work required on site has been reduced and some tasks that would have been “left behind” can be addressed. “We can now get rid of copper pole leases that we are not using efficiently, or there is a better design opportunity,” he added.

AI systems used on AT&T’s network can range from basic three-layer models to highly complex neural networks, commercial open-source GenAI engines, and large language models (LLMs), Savoor explained. AT&T has been using statistical methods and machine learning (ML) for “many years,” which have laid the foundation for these GenAI advancements.

“The opportunity with GenAI, especially with the deep learning models built in, is that we can apply these techniques much faster, especially for geospatial data and other visualizations,” Savoor said. “We’re building on what we already have. In many cases, we’re not starting from scratch, but we’re enhancing existing AI and machine learning capabilities.”

AT&T’s Path to Autonomy

AT&T has adopted GenAI with a “very opportunistic” approach, with use cases numbering in the hundreds. However, the company is strategically prioritizing implementations that deliver the greatest short- and long-term benefits.

The ultimate goal is to achieve an autonomous network, capable of operating with minimal human intervention. Savoor said the company has been progressing toward this vision for years, with some areas already demonstrating high levels of closed-loop autonomy (without human intervention).

This work is happening “at all levels of the network,” he added, particularly with localized autonomous capabilities rather than a “SkyNet” approach.

This includes the development of localized capabilities that enable intelligent decision making at the node level, such as energy savings.

The company focuses on integrating automation where it makes the most sense, based on scale and maturity of the technology.

For example, as new features such as its RAN in the cloud Once deployed, they will offer high autonomy from the start, thanks to advanced local intelligence in disaggregated components, Savoor explained. Meanwhile, existing technologies like LTE, which currently rely on partial automation but still require manual provisioning and configuration, will see more gradual improvements as they go through their natural upgrade cycles.

As a result, AT&T’s incremental GenAI installations will coincide with other network transformation activities, Savoor noted. “The investment you want to make on legacy, you balance that by saying, okay, where do you want to find the right automation for the right technology scale?” he concluded.