Transaction Network Services has released a white paper in collaboration with Kaleido Intelligence, addressing the rising energy demands facing telecom networks as artificial intelligence infrastructure expands.
The report outlines how increasing compute requirements are placing pressure on power consumption, cost structures, and operational planning across communications service providers.
AI Drives Sharp Increase in Energy Demand
The paper points to a projected rise in global data center power demand of up to 50% by 2027 and as much as 165% by 2030.
This growth is linked to the scaling of AI models, which require higher levels of computational power and supporting infrastructure.
Telecom operators face additional pressure from ongoing investments in 5G, 6G, and fiber networks.
These developments place energy consumption at the center of operational planning.
James Moar, Principal Analyst at Kaleido Intelligence, commented, “AI is forcing a power reality check across telecom. As compute demand explodes, energy is quickly becoming the industry’s most unforgiving growth limiter.”
Energy Management Becomes Operational Priority
The report identifies energy consumption as a primary cost driver for telecom operators, requiring more detailed monitoring of infrastructure and equipment usage.
Operators must assess where assets are deployed and how much power they consume to manage both cost and regulatory expectations.
Fragmented visibility across networks is identified as a barrier to effective energy management.
This creates challenges in aligning operational efficiency with sustainability targets.
Moar said, “CSPs cannot manage what they cannot see, and fragmented network intelligence is now a direct threat to margins and sustainability goals.”
White Paper Focuses on Standardization and Visibility
The white paper introduces a framework centered on standardizing network data across systems and vendors.
This approach aims to provide a unified view of infrastructure, enabling more consistent planning and resource allocation.
Improved visibility into power usage is positioned as a prerequisite for controlling operational costs.
The report suggests that firms adopting standardized data models may gain an advantage in managing scale.
Webinar to Address Network Planning Challenges
TNS and Kaleido Intelligence will host a webinar on May 6 to discuss the findings and explore practical implications for telecom operators.
The session will examine how AI-driven workloads affect network planning, procurement, and operational efficiency.
Participants will include industry analysts and engineering specialists focusing on infrastructure optimization.
The discussion will also cover strategies for reducing energy consumption and improving sustainability outcomes.
Platform Positioned as Supporting Infrastructure Layer
TNS highlighted its TruOps Common Language platform as a tool for improving visibility into network assets and energy requirements.
The system provides real-time data on equipment characteristics, including electrical requirements and environmental conditions.
This information is intended to support more informed decision-making across departments and vendors.
The platform reflects a broader shift toward data-driven infrastructure management in telecom.
Mike O’Brien, Chief Product Officer at TNS, said, “The power required to run today’s AI-driven networks is growing at an almost unsustainable rate. For CSPs, managing energy consumption is no longer just a sustainability goal; it is a critical lever for controlling one of their largest operational expenses.”
Takeaway
The growth of AI infrastructure is turning energy consumption into a central constraint for telecom operators, affecting cost structures and network planning. While frameworks focused on standardization and visibility offer a path forward, the scale of projected demand suggests that energy availability and pricing could become limiting factors for both telecom expansion and broader AI adoption.
