Telecom operators are moving from AI experimentation toward a more difficult phase: rebuilding networks, operations and business models around autonomous systems. TM Forum’s Innovate Americas 2026, scheduled for October 6–7 in Dallas, will bring executives from AT&T, T-Mobile, Verizon and TELUS together with technology leaders to examine how AI, network automation and programmable connectivity can translate into measurable operational and commercial gains.
For years, telecom operators have talked about autonomous networks as the next stage of connectivity. The harder question has been how to make that vision work across sprawling environments that include radio access networks, fiber, cloud infrastructure, edge computing, satellite links and legacy OSS/BSS systems.
That question will be at the center of TM Forum’s Innovate Americas 2026, taking place October 6–7 in Dallas, Texas.
The industry event will bring together service providers, hyperscalers, technology vendors and enterprise technology leaders around a common problem: how to move artificial intelligence from isolated pilots into the operating machinery of telecommunications companies.
The speaker lineup includes senior executives from some of the region’s largest carriers, including Yigal Elbaz, Network Chief Technology Officer at AT&T; Andy Markus, AT&T’s Chief Data Officer; Ankur Kapoor, T-Mobile’s Chief Network Officer; and Himanshu Polavarapu, AVP of Enterprise Architecture & Technology Strategy at Verizon.
The agenda also includes technology and responsible-AI perspectives from Accenture, AWS Industries and TELUS.
The focus reflects a broader transformation underway across telecom. Operators are under pressure to reduce the cost and complexity of increasingly heterogeneous networks while improving customer experience and creating new sources of revenue.
AI is being positioned as a possible answer, but deploying AI inside telecom infrastructure is considerably more complicated than adding a chatbot to an existing business process.
A network operator needs AI to understand real-time network conditions, coordinate resources across multiple domains and make decisions without compromising reliability. That creates a demand for AI-native network automation, where intelligent systems can increasingly detect problems, determine appropriate actions and execute changes with limited human intervention.
TM Forum’s agenda puts this concept alongside cross-domain service orchestration.
That is significant because modern connectivity services increasingly cross technological boundaries. A customer might depend on fiber for one segment, cloud resources for another, edge computing for latency-sensitive applications and satellite connectivity for locations outside terrestrial coverage.
Managing those environments independently creates operational silos.
The industry is therefore moving toward orchestration layers capable of treating networks as programmable resources rather than fixed collections of infrastructure.
TM Forum says Innovate Americas will explore automation across fiber, cloud, edge, core, RAN, OSS/BSS and satellite. In practice, the goal is to create services that can be dynamically provisioned and optimized across multiple network domains.
The concept also aligns with the development of network APIs.
Telecom operators have increasingly looked at exposing network capabilities—such as quality-of-service controls, location and identity services—to developers and enterprise customers. If network capabilities become programmable, operators can potentially move beyond selling connectivity toward offering application-aware infrastructure.
That creates a potential new monetization model.
For example, an industrial company could request connectivity with specific latency or reliability characteristics for an automated facility. A cloud provider could dynamically coordinate network capacity for a distributed workload. A logistics company could combine terrestrial connectivity with satellite coverage as vehicles move beyond conventional network boundaries.
The Innovate Americas agenda’s focus on everywhere coverage and connectivity continuity reflects this convergence. 5G and fiber remain central, but non-terrestrial networks (NTN), direct-to-device satellite and hybrid terrestrial-satellite architectures are expanding the definition of network coverage.
Satellite connectivity is particularly important because it changes the geographic assumptions underlying traditional telecom infrastructure. Operators no longer necessarily need to build terrestrial infrastructure everywhere they want to provide service.
But broader coverage introduces another orchestration problem: networks need to determine which connectivity layer should serve a user or device at a particular moment.
AI could become part of that decision-making layer.
The opportunity is not limited to operational efficiency. TM Forum is also putting AI monetization and programmable networks on the agenda.
That reflects a growing realization among operators that reducing costs alone may not be enough to justify the scale of AI investment required. Telecom companies need to identify services that turn network intelligence into revenue.
The challenge is substantial. Network operators operate in markets with high infrastructure costs and intense competition, while many conventional connectivity services are increasingly commoditized.
AI could help operators differentiate through more intelligent service assurance, personalization, automation and enterprise connectivity.
But the industry also has to contend with the risks of putting autonomous systems into critical infrastructure.
Responsible AI will therefore be part of the discussion. The presence of Arnab Chakraborty, Accenture’s Chief Responsible AI Officer, and Pamela Snively, TELUS’s Chief Data and Trust Officer, reflects the importance of governance, data quality, accountability and security as operators increase AI’s role in operational decisions.
This is particularly relevant because telecom networks have traditionally been engineered around deterministic behavior. Autonomous AI systems introduce probabilistic components into environments where outages can affect millions of customers.
That creates a tension at the heart of the AI-native telco: operators want more automation, but they also need tighter control over what automated systems are allowed to do.
The result is likely to be a gradual transition rather than a fully autonomous network appearing overnight.
Human operators will continue to define policies, constraints and escalation paths, while AI increasingly handles monitoring, optimization and routine remediation inside those boundaries.
TM Forum’s collaborative Catalyst projects are intended to demonstrate how those concepts can be translated into working technology. The organization says Innovate Americas will feature the region’s first collaborative innovation showcase of Catalyst projects.
For telecom executives, the event therefore offers a useful snapshot of where the industry is heading.
The question is no longer whether AI will become part of telecom operations. It is how deeply AI will be integrated into network control, service orchestration, customer operations and commercial systems—and whether operators can turn that integration into measurable business value.
The companies that succeed will likely be those that treat AI not as another application layer, but as part of the operating architecture of the network itself.
Market Landscape
The telecom AI market is moving across several interconnected layers:
AI infrastructure → network automation → service orchestration → autonomous operations → programmable networks → AI-driven monetization.
Large operators such as AT&T, T-Mobile, Verizon and TELUS are simultaneously modernizing network infrastructure and experimenting with AI-enabled operational models.
Hyperscalers such as AWS, Microsoft Azure and Google Cloud are increasingly involved because telecom networks are becoming more cloud-native, while vendors such as Nokia and Ericsson remain central to the underlying network infrastructure.
The competitive challenge is no longer simply deploying 5G. Operators need to coordinate multiple technologies while keeping service quality predictable.
That makes several areas strategically important:
- Autonomous network operations: AI-assisted detection, optimization and remediation.
- Cross-domain orchestration: Coordinating RAN, core, fiber, cloud, edge and satellite resources.
- Network APIs: Turning connectivity capabilities into programmable services.
- Non-terrestrial networks: Extending connectivity through satellites and direct-to-device services.
- Responsible AI: Establishing governance and safeguards around automated network decisions.
- AI monetization: Creating enterprise services and new revenue streams from network intelligence.
For telecom CIOs, CTOs and network architects, the biggest challenge is integration. AI models can be impressive in isolation, but network automation requires reliable data, standardized interfaces, policy controls and operational observability.Top Insights
- TM Forum’s Innovate Americas 2026 will focus on AI-native telecom operations, bringing major carriers together to examine autonomous networks and measurable business impact.
- Cross-domain orchestration will be central as operators connect fiber, cloud, edge, RAN, core, OSS/BSS and satellite infrastructure into programmable services.
- AI monetization is becoming a strategic priority as carriers seek new enterprise revenue streams from network APIs, automation and service intelligence.
- Direct-to-device satellite and hybrid terrestrial-satellite architectures are expanding coverage models while creating new challenges for network orchestration and service continuity.
- Responsible AI, data governance and human oversight will become increasingly important as autonomous systems gain greater influence over telecom network operations.
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