---
title: American Tower and PowerX partner to optimise energy use in Africa - Developing Telecoms
description: American Tower Corporation’s African subsidiary ATC Africa and PowerX have announced a strategic partnership that, they say, will bring the efficiency and environmental benefits of PowerX’s artificial intelligence (AI) solutions to Africa’s telecommunications industry by optimizing energy usage at tower sites.
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date: 2022-11-07T16:38:53Z
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American Tower Corporation’s African subsidiary ATC Africa and PowerX have announced a strategic partnership that, they say, will bring the efficiency and environmental benefits of PowerX’s artificial intelligence (AI) solutions to Africa’s telecommunications industry by optimizing energy usage at tower sites.

American Tower is a leading independent owner, operator and developer of multitenant communications real estate. PowerX says it is the first solution to put data intelligence at the heart of tower management decisions.

After a successful joint programme, ATC Africa has employed PowerX’s AI analytics across a select number of sites in Burkina Faso, Kenya, Niger, Nigeria and Uganda.

PowerX says that rollout of its AI platform has brought enhanced insight into the power management and analysis of ATC Africa’s sites. The platform leverages PowerX’s ability to analyse data to optimize ATC’s site performance, ensuring maximum greenhouse gas (GHG) emissions reduction.

ATC Africa says it is committed to providing connectivity while substantially reducing reliance on fossil fuels through the deployment of new sites that adhere to low GHG emissions site specifications in accordance with its science-based targets. To date it has invested over $300 million in energy efficiency improvements, renewable energy deployments and energy storage solutions to reduce the use of fossil fuels at its sites.

As PowerX’s CEO, Andrew Schafer explains, “AI-driven analytics uniquely lead the way in efficiently managing power and providing accurate and auditable records in environmental sustainability such as how much diesel and GHG emissions have been eliminated from site operations. We apply sophisticated machine learning and pattern recognition tools to existing site data to identify inefficiencies and anomalies previously buried deep in fragmented data sets.”

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