Econet Deploys AI to Slash Diesel Expenditure by 30%
Econet InfraCo, the tower infrastructure subsidiary of Econet Wireless Zimbabwe, has recorded a 30 per cent reduction in diesel expenditure after deploying an artificial intelligence (AI)-powered fuel management system designed to optimise generator usage across its telecommunications infrastructure.
The company said the technology, known as AI Fuel Mode, was developed in partnership with Cassava Compute, a sister company, to analyse generator operating patterns and improve fuel consumption efficiency.
The development marks a significant application of AI in telecommunications infrastructure management, particularly in Africa, where unreliable electricity supply has forced mobile network operators and tower companies to depend heavily on diesel-powered generators to keep their facilities running.
Econet InfraCo said it had become the first company in Africa to deploy an AI solution specifically designed to manage fuel efficiency in tower operations. It also described the platform as the first of its kind to be deployed by a tower operator globally.
The company’s chairman, Godfrey Gomwe, disclosed the cost savings in a statement accompanying its latest half-year financial results, noting that the technology was helping the business manage one of its largest operating expenses.
“By using AI to analyse how and when each diesel generator is deployed, we have developed a fuel management system that has reduced our diesel costs by 30 per cent. This demonstrates the practical value of AI in improving operational efficiency and managing one of our largest expenses,” Gomwe said.
The reported savings come at a time when energy costs remain a major concern for businesses that depend on continuous power supply. Geopolitical tensions and conflict in the Middle East have also heightened concerns about fuel price volatility, putting additional pressure on companies whose operations rely on diesel generators.
For telecommunications operators, uninterrupted power supply is essential to maintaining mobile network availability, supporting data services and ensuring that customers can communicate even when public electricity supplies fail.
However, the cost of powering telecommunications infrastructure can be substantial, particularly in markets where electricity supply is unreliable and operators must maintain generators at numerous locations.
Econet InfraCo estimates that more than 500,000 generators support mobile network operations across Africa, illustrating the industry’s extensive dependence on diesel and the potential financial benefits of improving fuel efficiency.
The company said the AI Fuel Mode platform was developed after Econet InfraCo and Cassava Compute analysed generator deployment patterns to identify opportunities to reduce fuel consumption.
Their work produced an AI-based fuel management matrix designed to determine how and when generators should be operated more efficiently.
By analysing generator usage, the system is intended to help operators optimise deployment decisions, reduce unnecessary fuel consumption and lower operating costs without compromising the power requirements of telecommunications infrastructure.
The collaboration also highlights the growing role of AI computing in addressing practical business challenges beyond conventional applications such as customer service, data processing and software development.
The platform was developed using Cassava Compute’s NVIDIA-powered AI computing infrastructure in Cape Town, South Africa.
NVIDIA’s computing technology supports the processing capabilities required for AI applications, while Cassava Compute provides the infrastructure used to develop and deploy the solution.
Econet InfraCo’s experience could provide a model for other tower infrastructure companies seeking to reduce their exposure to diesel price fluctuations and improve operational efficiency.
Cassava AI plans to make the platform available to other operators, potentially extending its benefits across the telecommunications industry and into other sectors with significant energy requirements.
Mining and manufacturing companies have been identified as possible beneficiaries because their operations frequently require substantial power supplies and may depend on generators where grid electricity is insufficient or unreliable.
Wider adoption of AI-driven fuel management could help such businesses improve energy planning, reduce avoidable fuel expenditure and make better use of existing equipment.
However, the extent of the benefits for other operators would depend on factors including their power infrastructure, generator operating patterns and the conditions under which the technology is deployed.
Beyond diesel consumption, Econet and its technology partners are also exploring ways to apply AI to electricity management across mobile telecommunications networks.
Cassava AI, working with NVIDIA, is beginning the deployment of a related platform called AI Energy Mode to help Econet Wireless optimise electricity consumption across its mobile network.
While AI Fuel Mode focuses on improving the efficiency of diesel generator operations, AI Energy Mode is designed to optimise the use of electricity across the network.
The two initiatives reflect a broader effort to use AI to address energy management challenges and reduce the cost of operating telecommunications infrastructure.
For Econet InfraCo, the reported 30 per cent reduction in diesel expenditure provides an indication of the potential financial returns from applying AI to routine operational decisions.
The company also expects the deployment of both platforms to increase demand for graphics processing unit (GPU) computing capacity at Cassava’s AI factory.
GPU computing capacity is an important component of modern AI infrastructure, enabling the processing of large volumes of data and the execution of computationally intensive AI workloads.
The initiatives demonstrate how AI technology is increasingly being applied to energy-intensive industries, where improvements in efficiency can translate into significant cost savings and more effective use of resources.
