Telecommunications companies are uniquely positioned to drive growth in the AI economy. Artificial intelligence, now widely recognized as the defining technological shift of our era, demands unprecedented amounts of computing power and energy. Yet one persistent challenge limits AI’s potential: the need for timely, high-quality data to fuel models in real time.
Today’s advanced AI models consume enormous energy—comparable to the annual usage of hundreds or thousands of households—yet a significant portion of that compute capacity remains underutilized because the right data streams are not available. Estimates show that roughly 40% of compute resources allocated to AI can sit idle due to insufficient data access, and more than 65% of AI projects are delayed or fail because of data bottlenecks.
Telcos, with their extensive infrastructure and visibility into global data flows, can help close this gap. Handling around 180 zettabytes of data traffic annually, telecom operators can move beyond pure connectivity and become vital enablers of AI innovation by unlocking and monetising the data that already moves across their networks.
The AI Data Paradox: Compute Without Content
AI models are advancing quickly across natural language processing, computer vision, predictive analytics and more. However, model performance hinges on access to high-quality, real-time data. When data pipelines are incomplete or poorly designed, added compute power translates to limited gains. This mismatch wastes resources and impedes practical innovation.
Telcos have a distinctive advantage: their networks generate and carry vast, diverse data streams—from smart city sensors and industrial IoT deployments to mobile consumer devices. Industry analysts estimate that a large share of the world’s collected data remains unused, often described as “dark data.” By activating and responsibly exposing these assets, telecom operators can convert idle compute into productive AI workloads.
The Untapped Goldmine: Telco Data Streams
As global data traffic surges, telcos sit at the centre of that expansion. Connected devices and IoT ecosystems will increasingly produce real-time data; forecasts suggest that by 2025 a substantial majority of generated data will be produced at the edge. Historically, much of this data has been treated as a byproduct of connectivity rather than a strategic asset. That view is shifting: operators now recognise the commercial and technical value of their data when combined with AI.
Key Opportunities for Monetisation:
- Real-Time Data for AI Training: AI applications—such as conversational agents, autonomous systems and predictive analytics—require continuous, up-to-date data. Telcos can package anonymised, aggregated data feeds to accelerate model training and improve accuracy for developers and enterprises.
- Partnerships for Edge Computing: The rollout of 5G enables edge-based processing with low latency. By offering edge compute and storage close to data sources, telcos can support latency-sensitive AI workloads and tap into a large enterprise market for distributed computing services.
- AI-powered Services for Enterprises: Combining network data with AI capabilities allows telcos to offer value-added services—such as hyper-personalised customer engagement, advanced analytics and predictive maintenance for industrial customers—helping enterprises reduce costs and improve performance.
- Energy Optimisation Solutions: Given AI’s high energy footprint, telcos can apply AI-driven insights to optimise their own networks for efficiency and carbon reduction. These optimisation capabilities can also be packaged and sold to enterprise customers facing similar sustainability and cost pressures.
Challenges on the Road Ahead
Despite significant opportunity, telcos must navigate several key challenges. Data privacy and security top the list: as custodians of sensitive user and network data, operators must comply with complex regulations and adopt transparent handling practices to build trust with customers and partners.
Interoperability and scalability present further hurdles. To serve diverse AI workflows, telco platforms and pipelines must be compatible with a wide range of AI frameworks and tools while scaling to meet surging demand. Achieving this requires robust APIs, standardised formats and flexible infrastructure.
Finally, a cultural and organisational shift is needed. Moving from a connectivity-first mindset to a data-centric business model requires new talent, training, governance, and business processes. Strategic investment in people and capabilities will be essential for telcos that aim to capture this new market.
Why 2025 Is an Inflection Point
Several converging trends point to 2025 as a pivotal year for telcos aiming to become AI enablers:
- Maturation of AI Ecosystems: AI technologies are maturing into reliable, commercially valuable tools, driving demand for steady, high-quality data streams.
- 5G Expansion: The continued deployment of 5G networks gives operators the low-latency, high-throughput infrastructure required for many AI applications.
- Growing Focus on Sustainability: As the energy implications of AI gain attention, operators can offer optimisation services that help reduce consumption and support corporate sustainability goals.
- Enterprise Adoption of AI: Organisations across sectors are embedding AI into decision-making and operations, increasing demand for dependable, real-time data sources.
Telcos as AI’s Data Buffet
By 2025, telecom operators have the potential to shift from being mere data carriers to becoming the primary providers of the high-quality data that AI systems need. Unlocking and monetising these data assets will not only create new revenue streams but also redefine the role of telcos in the digital economy.
The companies that embrace this transformation will accelerate AI innovation and secure leadership in a data-driven landscape. The future of AI and the future of telecom are increasingly intertwined; together they will drive the next wave of technological progress and reshape industries worldwide.
Photo by Nick Fewings on Unsplash
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