Missed It Live? Watch When AI and Energy Collide On Demand

Data centers are consuming electricity at a staggering rate — demand shot up 17% in 2025, while global electricity use grew just 3%, according to the International Energy Agency (IEA). Add to the mix that global power demand from data centers is forecasted to increase 50% by 2027 and by as much as 165% by 2030, and you can see how immense pressure is being put on energy consumption and the power grid.

These statistics also capture the scale of the challenge now facing Communications Service Providers (CSPs). As AI workloads continue to multiply, this burgeoning energy demand is climbing at a pace that threatens margins, complicates network planning and reshapes the economics of telecom infrastructure.

To help CSPs respond, TNS and Kaleido Intelligence recently hosted the webinar When AI and Energy Collide: How a Common Language Framework Can Help CSPs with Network Management, Efficiency and Planning. Now available to stream on demand, the session features James Moar, Principal Analyst at Kaleido Intelligence, Juan Carlos Ortiz, Director of Global Solutions Engineering at TNS and George Malim, Managing Editor of Agile Telco.

A central theme emerged: CSPs cannot manage what they cannot see. With energy already representing a major share of network operating expenses, visibility into power consumption, equipment specifications and environmental conditions is now a competitive differentiator. Standardized, unified data can help CSPs operationalize energy strategy at scale.

A Snapshot of Key Discussion Highlights

The panel explored where rising network and energy costs originate — from 5G and 6G rollouts to fiber expansion and AI-powered services. They also discussed why data fragmentation limits effective decision-making, and how a Common Language framework can enable transparency across assets, locations and equipment. The framework offers a valuable basis for capturing and analyzing key energy attributes including power usage, heat dissipation, altitude tolerance, humidity tolerance and minimum and maximum operational and storage temperatures. This clarity can support CSPs in making smarter procurement and planning decisions as well as complementing existing energy monitoring and management systems.

As Ortiz explained, “Since we have islands of information where it is very difficult to harmonize the data among them, therein lies the challenge. Not only can the lack of uniformity in the data lead to confusion in terms of where the source of truth is, but the inability to really leverage this data inhibits the ability to make decisions related to energy network management or other aspects of the business. Given these needs, that is where the concept of Common Language comes into play.”

Download the White Paper

To complement the discussion, Kaleido Intelligence’s new white paper, Optimizing Network Planning for the AI Era with Common Language, is now available for complimentary download. The paper offers insights for CSPs working to balance AI-driven growth with energy realities, efficiency, goals and cost pressures.

Together, the webinar and white paper give telecom leaders a practical roadmap for exploring how visibility into network equipment and locations can become an advantage at a time when energy has become a growing constraint on industry expansion.