GSMA Luis Powell and TM Forum's Andy Tiller highlight a new collaboration to help the industry reduce fragmentation and accelerate the practical adoption of AI in telecommunications.
Artificial intelligence is now a management-level priority across the telecommunications industry. Operators are investing, providers are innovating, and the broader ecosystem is moving quickly. However, despite this push, telecommunications continue to face structural barriers that make AI implementation much more complex than in many other industries.
Telecommunications is one of the most difficult environments for AI to transform. Networks are multi-vendor, highly fragmented, and dependent on siled data, with very little tolerance for error. To be useful in this context, AI must be accurate, efficient and reliable from day one.
Current frontier models are not designed for telecommunications. They are not trained in telecom-specific data and often struggle with the language, architecture, and operational realities of networks. As a result, deployments remain focused on customer experience and business functions, rather than the network layer itself. GSMA Intelligence data shows that only 16% of AI deployments are targeting networking use cases, despite networks accounting for 34% of OPEX, as cost pressures and ROI expectations continue to rise.
That's why telecoms need to collaborate and align to solve these challenges themselves, creating AI approaches that reflect the complexity, economics and operational realities of the industry.
Closer collaboration between GSMA and TM Forum
The shared challenge is clear: telecoms need AI that understands telecoms and a clearer path from experimentation to deployment at scale.
This is where deeper collaboration between GSMA and TM Forum adds real value, addressing complementary parts of the same challenge.
Through the Open Telco AI initiative, GSMA is focused on developing telecom-grade AI; agent models and systems that are accurate, efficient and reliable. That means creating a shared foundation of telecom models trained on specialized telecom datasets, such as the OTEL family of models, and benchmarks that demonstrate how these models perform on real telecom tasks.
TM Forum focuses on high-value frameworks, standards and use cases that align the industry on what should be built, how it should interoperate and where value should be created first. Its autonomous networks and trusted data and AI missions create frameworks for scaling AI within its open digital architecture (ODA), along with solution packages for high-value scenarios and standardized tools to measure progress. The Catalyst and Innovation Hub projects create proofs of concept and reference implementations to implement these solutions.
It is about connecting the AI stack end-to-end, combining shared models, common frameworks and practical implementation paths, with the trust necessary for critical network environments.
The combined approach is already having an impact
The goal of closer collaboration is to reduce fragmentation and accelerate industry-wide adoption by bringing these elements together in a more coherent way. The impact is already visible.
Philippine mobile network operator Globe Telecom is exploring multi-vendor RAN root cause analysis using TM Forum's technical solution packages to help expose normalized APIs across vendors, while also working with Open Telco AI on the models and agents needed to automate the analysis.
Similarly, AT&T's OTEL models, specialized models for telecommunications, are being adapted to TM Forum environments such as Model-as-a-Service (MODaaS) and ODA Canvas, transforming proven, carrier-grade AI into standardized, interoperable assets that the broader telecommunications industry can adopt and scale in multi-vendor cloud-native environments.
These examples are important because they tangibly demonstrate end-to-end alignment, from use case definition to model development and deployment. It shows how AI can move beyond isolated innovation, towards interoperable AI models designed to operate within established industrial frameworks. And it is a collaborative ecosystem where operators, suppliers and partners can help shape shared solutions instead of navigating disconnected efforts in parallel.
Telecommunications are at the heart of the AI economy.
Networks underpin the cloud, device, and edge capabilities that AI depends on. However, telcos themselves have not fully grasped the value of AI within their own operations.
If the industry wants to accelerate toward more autonomous and AI-native networks, it must align on shared assets, common standards, and practical implementation paths.
That is why this collaboration is important now. The industry cannot depend on generic tools and fragmented progress. You need a shared and trusted foundation. That means participating in the Open Telco AI and TM Forum initiatives, contributing to the definition of use cases, model development and validation, and helping to shape the standards, frameworks and architectures that will determine whether AI delivers real value in telecom networks.
The opportunity is significant. But unlocking it requires alignment as well as ambition. GSMA and TM Forum are committed to offering both, and this is just the beginning, there will be more throughout the year on data, models, assessments and member proof points.
Look out for more information on telecoms AI at TM Forum and at this week's GSMA events.
Turn on DTW in Copenhagen opens its doors today, where TM Forum will highlight trusted AI, autonomous networks, and real-world member exhibits demonstrating how AI-native telecommunications can move from concept to execution.
and in Shanghai CMM (June 24-26), GSMA will bring together industry innovators at the GSMA Pavilion and through Open Telco AI sessions focused on creating telecom-grade AI benchmarks and practical implementation pathways.
