By Emmanuella Opara | November 10th 2026
KEY POINTS
- The GSMA says telecom operators can generate additional revenue by helping businesses and consumers access, manage and optimise artificial intelligence services.
- More than 200 operators globally are already offering enterprise AI tools, including copilots, productivity applications and industry-specific solutions.
- AI tokens are emerging as a new measure of digital consumption, creating opportunities for operators to develop pricing and billing models.
- The association says operators must move beyond reselling AI access and build platforms that help customers control costs, select models and manage workflows.
MAIN STORY
Telecommunications operators could expand their revenue beyond voice and data services by providing platforms that help businesses and consumers access and manage artificial intelligence tools, according to the Global System for Mobile Communications Association.
The industry body said the growing use of AI applications, automated workflows and AI agents was creating commercial opportunities for operators to participate more directly in the technology value chain.
In an analysis published on its website, Kenechi Okeleke, Director of Regional, Social and Policy Research at GSMA Intelligence, said operators had traditionally concentrated on using AI to improve internal efficiency but could now turn the technology into a source of direct revenue.
He explained that the increasing use of AI models was introducing tokens as a new measure of digital consumption, similar to how telecommunications companies previously charged customers for voice minutes and mobile data.
However, unlike gigabytes, the value of tokens depends on factors such as the AI model being used, the complexity of a task and whether the tokens relate to input, output, cached context or reasoning.
Okeleke said operators that could simplify these technical complexities and package AI services around customer requirements would be better placed to benefit from the emerging market.
The GSMA analysis identified three areas in which telecommunications companies were developing AI capabilities: infrastructure, models and solutions.
At the infrastructure level, operators are investing in data centres, cloud services, fibre networks and edge infrastructure to support AI factories, sovereign AI platforms and graphics processing unit-as-a-service offerings.
At the model level, some are developing foundation models or partnering with technology companies to produce systems suited to local languages and market needs.
The solutions segment has attracted the widest participation, with more than 200 operators worldwide already offering enterprise copilots, conversational AI, productivity tools and applications designed for specific industries.
Asia-Pacific accounts for 43 per cent of global telecom operator participation in AI infrastructure and 38 per cent in AI model development, according to the analysis.
China is emerging as an early market for commercialising AI consumption through telecommunications networks. Average daily token usage in the country rose from about 100 billion at the beginning of 2024 to 140 trillion by March 2026, driven partly by the growing adoption of AI agents and coding assistants.
The country’s three major telecom operators are testing different ways of earning from the demand.
China Telecom combines access to AI models with connectivity and cybersecurity services, while China Mobile packages AI tokens with cloud PCs and AI agent capabilities in regional offerings. China Unicom is exploring a credit-based system through which customers can manage token consumption across different AI models.
Okeleke cautioned, however, that China’s experience might not be directly replicated in other markets because of its extensive cloud businesses, investments in AI infrastructure and established ecosystem of open-weight models.
He said operators in other countries would need to develop commercial approaches suited to their infrastructure, customer base and competitive conditions.
Beyond selling access to AI tokens, the analysis identified the control layer as a potentially more sustainable source of revenue.
This would involve helping businesses manage AI services across different providers and models by selecting suitable systems for specific tasks, directing workloads, controlling costs and meeting governance requirements.
The report outlined three stages for developing these capabilities: model aggregation, intelligent routing and workflow optimisation.
Model aggregation brings different AI models together through a single interface, application programming interface and billing system. Intelligent routing enables customers to select models based on cost, quality, speed, availability and regulatory requirements.
Workflow optimisation, meanwhile, focuses on ensuring that businesses translate AI adoption into measurable productivity gains and cost savings.
Citing examples, Okeleke said China Mobile’s MoMA platform could reduce token costs by between 20 and 30 per cent through intelligent routing, caching and context reuse.
He also referred to reported savings of up to 90 per cent achieved by AT&T through its internal AI gateway, suggesting that telecom operators could first demonstrate the value of such platforms within their own operations before offering them to customers.
The GSMA said operators had existing advantages that could support their entry into the market, including established customer relationships, billing and identity management systems, security and compliance expertise, local regulatory knowledge and distributed infrastructure.
However, it warned that operators faced competition from hyperscalers, cloud service providers and AI-focused companies already building platforms to manage access to artificial intelligence services.
Okeleke said telecom companies needed to determine their positions in the AI value chain, develop the necessary capabilities and establish partnerships without becoming low-margin resellers.
He also urged operators to prepare their networks for changing AI traffic patterns, including potentially higher uplink requirements and more distributed processing. Network application programming interfaces and edge capabilities could also help them differentiate their services.
The analysis warned that the opportunity to secure a meaningful share of the AI economy was narrowing as technology companies moved quickly to establish their positions.
THE ISSUES
The expansion of AI services is creating a potential new business market for telecommunications operators, but the opportunity extends beyond providing internet access or reselling subscriptions to AI platforms.
The emerging competition is over who controls the systems through which businesses access AI models, manage consumption, direct workloads and measure the value generated by the technology.
For telecom operators, their existing customer relationships, billing infrastructure and network capabilities could provide an entry point. However, competing with established cloud and AI companies will require investment, technical expertise and commercially viable partnerships.
WHAT’S NEXT
Telecom operators will need to determine which parts of the AI value chain they can compete in, develop the required infrastructure and services, and establish partnerships with AI providers. Their ability to offer cost management, model selection and workflow optimisation could determine how much revenue they capture from growing AI demand.
BOTTOM LINE
AI is creating an opportunity for telecom operators to move beyond connectivity and participate in the services built around artificial intelligence. The GSMA’s analysis suggests that operators able to manage AI access, costs and business applications could secure a larger role in the expanding market, while those that remain connectivity providers risk losing value to technology companies controlling the AI service layer.
