MTN Group is aiming to generate approximately $1.8 billion (about R30 billion) in value from artificial intelligence initiatives over the next three to five years, with around half of that expected to come from improving operational efficiency and reducing costs.
The remainder is projected to be derived from consumer-focused and enterprise AI services. Based on an exchange rate of roughly R1 = $0.06.
Speaking at the company’s capital markets day, MTN Group Chief Technology and Information Officer Charles Molapisi said the operator’s primary focus would be on using AI to improve internal operations, an area where management has the highest level of confidence. The company will adopt a more measured approach towards commercial AI infrastructure services, which require significant capital investment and carry greater risk.
MTN has structured its AI strategy around three key pillars. The first, AI Inside, focuses on using AI across the business, including network operations, energy management, finance, human resources, legal services and fraud detection. The second, AI for B2C, aims to drive revenue growth through highly personalised consumer offerings. The third, AI for B2B, seeks to provide computing power, graphics processing units (GPUs) and edge computing services to enterprise customers.
Each pillar is assessed using different performance metrics. AI Inside is evaluated based on operating cost reductions and avoided capital expenditure. AI for B2C is measured through customer adoption and service economics, while AI for B2B is viewed as the largest long-term opportunity, although it remains highly dependent on energy costs, AI processing economics and competitive market dynamics.
According to Molapisi, MTN’s immediate priority is tackling its cost base. Network and IT operations account for roughly 55% of the group’s operating expenditure and around 80% of capital expenditure, making them the most significant opportunities for value creation. Energy management has emerged as one of the company’s most important targets.
Several AI-powered solutions are already operational. These include energy optimisation systems that manage power consumption at base stations, autonomous network agents that identify and resolve incidents, fibre monitoring technology capable of detecting ground disturbances before cable damage occurs, and AI-driven capital expenditure planning tools that forecast traffic demand and revenue potential to guide network investments.
Within corporate functions, MTN is consolidating legal contracts into a central repository, enabling AI systems to draft documents, recommend amendments and monitor regulatory developments.
On the consumer side, the company’s flagship AI platform, NBx 2.0, delivers personalised recommendations and offers using advanced customer insights. The system is currently active across South Africa, Nigeria, Ghana, Cameroon, Zambia and Uganda, serving around 44 million customers, with plans for broader deployment. Supporting initiatives include Telco GPT, an AI assistant for customers and call centre agents, and Zigi, a conversational AI platform that operates through both text and voice in local languages.
One of the most prominent examples of AI deployment is in Nigeria’s SIM registration process. Previously, more than 200 employees manually verified customer records by matching biometric information against national databases. MTN has replaced much of that work with 13 AI agents powered by computer vision technology, significantly improving processing speed and accuracy. The system is now being expanded to Cameroon, Côte d’Ivoire, Eswatini, Ghana and Zambia, while maintaining governance controls and human oversight.
The company is also using AI for revenue assurance, analysing more than 10,000 data points across billions of daily transactions to identify anomalies that would be difficult for human teams to detect.
To measure progress, MTN has developed an internal “AI intensity” framework with targets extending to 2028. Across its six largest markets, the company expects 80% of AI-generated bottom-line benefits to come from AI Inside initiatives. Achieving this goal will require 70% of employees to receive AI training, 40% penetration of AI models and autonomous agents, and 80% maturity in supporting technology and operational processes.
While MTN continues to pursue opportunities in consumer and enterprise AI, the company believes the most reliable and immediate returns will come from using artificial intelligence to enhance its own operations and improve efficiency across the business.
