Telecom Operators Seek Routes to AI Monetization Beyond Connectivity

The telco commercial AI opportunity

Over the last two years, the AI boom has spurred national sovereign initiatives for control and autonomy over intelligence and data. Businesses are constructing massive new data centers to provide more local performance, and to comply with governments' national and regional interests. There is tight competition for back-ordered AI processing infrastructure from vendors. Expert talent to build and operate AI infrastructure is scarce.

For network operators, building AI infrastructure and selling AI services is a major new commercial opportunity. Carriers have four types of opportunities for commercial services that fuel the AI revolution:

• Network connectivity and interconnection. Carriers provide high-capacity services — wavelengths, Ethernet, IP transit, and dark fiber — to hyperscalers, neoclouds, data centers and businesses. Omdia forecasts that connectivity represents US$17–18bn of new, global addressable AI revenues for telcos by 2030.
• GPUaaS, colocation, and hosting. National carriers serve national interests. They can support sovereign AI infrastructure by building it themselves or teaming with partners. Telcos address AI issues such as national control over platforms and data, national security, and compliance. Omdia forecasts AI data center services represent US$3–4bn of new, global addressable AI revenues for telcos by 2030, a small but significant share relative to hyperscaler and neocloud wins.
• Performance and management. Carriers can offer premium features with AI connectivity: Orchestration, premium guarantees, dynamic capacity, managed infrastructure, and managed security. Omdia forecasts performance premiums represent less than US$1bn of new, global addressable AI revenues for telcos by 2030. Premium features will help influence and win over existing enterprise contracts.
• Innovation and applications. Carriers can develop their own AI models, provide professional services to businesses, and AI functionality to consumers. Omdia conservatively estimates less than US$1bn new revenues for telcos from these areas, but this vastly underplays the opportunity. The applications space is a wildcard with vast potential.

Omdia's tracking of network providers commercializing AI services shows that Connectivity is King. However, telcos are widely developing services and engaging in partnerships for AI platforms and functionality. They are sourcing their own hardware to provide services; they partner for AI functionality; and they are ramping up in-house platforms and expertise. Figure 1 shows the distribution of telco announcements for full-year 2025, showing where telcos are focusing their efforts.

Figure 1: AI connectivity is top for telcos, but the sum of services and applications is larger (Source: Omdia)

To date, Omdia has tracked more than 250 relevant AI announcements by telcos. Outside the two global poles of development (China and the USA), some telco-driven AI applications examples include video analytics in Latin America; robotic process automation (RPA) in the Middle East; healthcare applications in East Asia; talent management and transport security in Europe; and ecological monitoring in the UK.

Besides these customized AI functionality examples, telcos around the world frequently partner with AI-enabled platform and applications providers to bring functionality to their customers. The most common telco partnerships are for Generative AI and Agentic AI platforms; AI-enabled IoT; AI-enabled collaboration, contact center, and Communication Platform-as-a-Service (CPaaS); AI workforce management; and AIOps for managing networks and cyber security.

The current state of enterprise AI adoption

Figure 2: SMEs are making use of AI tools across sales,
marketing, IT, and operations (Source: Omdia)

About 8 out of 10 large enterprises (79%) and more than half (53%) of SMEs have adopted AI platforms and services. However, there is much more AI that enterprises use casually in day-to-day operations. Enterprise SaaS and analytics, IT and operations, customer contact center and collaboration, search tools and web surfing – these and more everyday commercial tasks are infused with AI functionality to make interactions easier and improve output quality.

Figure 2 shows where SMEs use AI tools to support their operations today. Adoption of AI tools in customer support (chatbots) and in cyber security grows with the size of the SME. The gap for AI adoption by company size is smaller in other areas, such as marketing and social media and in sales support. SMEs use AI tools for tasks such as generating content, identifying leads, writing and editing sales proposals and managing bids, and for tracking business performance.

Figure 3 shows leading enterprise applications that have integrated AI functionality among current large enterprise AI adopters. The most often AI-enabled applications are the internet of things (IoT), communications & collaboration, and business intelligence/analytics. By traffic volume, communications & collaboration also leads, but it is joined by cognitive analytics and HR/workforce software, which is increasingly becoming media- and collaboration-centric.

Figure 3: Large enterprises are widely adopting/planning
to adopt applications enhanced with AI (Source: Omdia)

Conversations with enterprises that have adopted AI showcase a wide and growing range of active projects. Organizations in Manufacturing, Energy, and Healthcare are among the most mature adopters. Industrial robotics and augmented reality technicians and training; analytics for geological exploration and seismic monitoring; intelligent patient scheduling, medical image diagnosis, surgical training and robotic surgery are just a few of the many rich AI applications on the table for these industries. Other sectors to embrace AI widely include financial firms; real estate management for smart buildings; utilities; and the transport industry.

The public sector is a less mature but critical adopter. Along with healthcare, finance, and utilities, public sector has sovereign (privacy and secure critical operations) concerns. Here, national telcos have a role as trusted stewards that keep sensitive AI data inside trusted boundaries. In partnership with government agencies and regulators, the telco role is expandable to secure AI infrastructure, hardware and platforms that host data being processed and at rest. For telcos that operate sovereign AI, their role expands to commercial businesses that work with the public sector and other regulated ecosystems.

The future of AI traffic in the enterprise ecosystem is fast growing: Enterprise AI adopters forecast their AI traffic to grow 3.4x over the next 18 months, and by 4.6x over the next 36 months. Figure 4 shows the top priorities in AI for large enterprises. Adopters are most concerned about scaling and integrating AI, and about satisfactory end-to-end performance. Finding talent and sourcing hardware are important secondary considerations.

Figure 4: Enterprises’ top challenges as they continue to develop their AI strategies (Source: Omdia)

Revenues are there, but telcos must seize them

Telcos see major revenue potential in supporting the rapid buildout of AI. What started in China and USA has spread to regional and national markets. Telcos provide the connectivity: fibering up data centers; interconnecting AI platforms with high-capacity links; handling capacity increases and traffic flow changes from B2B and B2C user and device AI traffic flows.

But there is more opportunity: A sovereignty role providing secure national connectivity; adding GPUs and other hardware; and hosting. Telcos may also plug talent gaps, providing services that help businesses adopt and use AI effectively.

Telcos can capture enterprise and public sector AI revenues through building, buying, or partnering. But for telcos to realize this opportunity they must take a leadership role working with governments, regulators, and partners. This way they can shape the domestic AI opportunity they are positioned to serve.