FutureNet Asia 2026: From AI experimentation to autonomous network operations

Blog — 23 Oct, 2026

FutureNet Asia 2026: From AI experimentation to autonomous network operations

Telecom operators are entering a period in which AI is shifting from an efficiency tool to a fundamental layer of network strategy. The implications extend well beyond automating operational processes: AI is beginning to influence how networks are architected, how capacity and resources are orchestrated, how services are delivered and, increasingly, where operators see opportunities to create new sources of value.

That transition was a central theme at FutureNet Asia 2026, held Sept. 22–23, 2026, in Singapore, where Asia-Pacific operators and technology providers explored the evolution toward AI-native and autonomous networks. Discussions around agentic AI, network automation, digital twins, data infrastructure and AI-driven operations highlighted both the scale of the opportunity and the complexity of moving from targeted use cases to production-grade deployments.

The Take

AI-native networks require operators to modernize the foundations beneath AI, including architecture, data, interoperability and orchestration.
Operators are beginning to move from isolated automation toward AI agents capable of coordinating decisions across network domains.
Scaling autonomy will depend as much on governance, control and measurable operational value as on the underlying AI technology.

Building the AI-native telco – Re-architecting the network from the ground up

In the keynote CxO panel, "Building the AI-Native Telco – Re-Architecting the Network from the Ground Up," executives from Axiata Group Bhd., Telstra Group Ltd. and Amdocs Ltd. argued that becoming an AI-native telco will require operators to address the foundations of their networks before they can fully capitalize on AI. Axiata's Thomas Hundt emphasized the need to simplify architecture, reduce legacy complexity and maintain modularity, while noting that AI can itself help accelerate the migration away from legacy environments. The urgency is underscored by the current maturity of network autonomy.

The discussion also underscored the growing importance of trust, security and control as autonomy increases. As AI agents take on greater responsibility across network operations, clearly defined policies, permissions and guardrails will be essential to prevent "automation blindness" and ensure that automated decisions remain subject to appropriate oversight.

Modernizing the network provides the foundation, but it does not by itself deliver autonomy. The next challenge is scaling intelligence across network domains and moving from individual automated processes toward systems capable of coordinating decisions more broadly.

Autonomous networks at scale – From automation to intelligence-driven operations

In the "Autonomous Networks at Scale – From Automation to Intelligence-Driven Operations" panel, experts from Axiata, Singtel Optus Pty. Ltd., True Corp. and Viavi Solutions Inc. focused on the industry's shift from proving individual automation use cases to scaling autonomy across the network. Fragmented legacy systems, inconsistent data and limited interoperability remain practical barriers. Digital twins were also highlighted as an important mechanism for testing and validating AI-driven changes before they are introduced into live networks, reinforcing the need for autonomy to develop within controlled and trusted environments.

That architectural shift raises a more immediate question: how will AI agents coordinate across increasingly complex network environments?

AI agents in action - Delivering value now

If the earlier sessions focused on the architecture required for autonomy, the "AI Agents in Action" panel offered a view of where operators are already applying these capabilities. Speakers from Vodafone Idea Ltd., Telkomsel, Telstra Digital Infrastructure and ServiceNow discussed applications spanning software development, network fault diagnosis, predictive maintenance, service assurance and enterprise operations.

FutureNet Asia 2026 indicates that the telecom AI discussion is becoming increasingly focused on execution. From an S&P Global Market Intelligence perspective, operators are moving toward more integrated forms of automation and intelligence, but the path to higher levels of autonomy remains dependent on foundational investments in architecture, data, interoperability and governance. The key question for the industry is therefore shifting from where AI can be applied to where it can be deployed reliably, at scale and with measurable impact on network operations and business outcomes.

Clients can access the full article here.

Clients can explore the S&P Global research series for further insights into AI-driven telco infrastructure across APAC.

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This article was published by S&P Global Market Intelligence and not by S&P Global Ratings, which is a separately managed division of S&P Global.