AT&T’s D-Wave quantum pact achieves new network efficiencies AT&T’s move to expand its use of D-Wave's quantum computing technology reflects the service provider’s plans to address optimization challenges across its network operations. An initial focus for AT&T is to layer D-Wave's annealing quantum computing technology into the tools that are already powering AT&T’s agentic AI solutions. D-Wave's quantum annealing technology is a specialized analog computing approach designed to solve complex optimization problems by letting physical systems naturally find their lowest energy state. For AT&T, agentic AI is about enhancing how it operates its network. Agentic tools in AT&T’s network are improving network operations like outage detection and management, reducing customer downtime by 12 million hours in 2025. Further, AT&T said that quantum capabilities could help increase the benefits of agents in AT&T’s network operations. “D-Wave’s annealing quantum computing technology gives us a new way to approach optimization and high-intensity compute challenges across AT&T’s network operations,” said Lucus Haugen, director, Data Science for AT&T’s Chief Data Office. New efficiencies A key focus for AT&T is centered around gaining new efficiencies. In one of its first applications, AT&T used D-Wave's technology to reduce the processing time for a network optimization workload from approximately one hour to less than 15 seconds. Based on these early results, AT&T plans to explore using D-Wave’s quantum computing technology across a broader set of applications, such as outage detection and response, technician routing, network build planning, and traffic management. Through these applications, AT&T said it will explore how faster processing could translate into faster and more accurate planning, as AT&T scales its converged fiber and 5G network to meet growing AI-driven demand. “The speed we’re seeing with D-Wave challenges what’s currently possible. It has the potential to help us optimize faster, increase efficiency and scale more real-time