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Building the foundation for AI-native ODA

This Innovation Hub Pioneer Project builds on the successful DTW Ignite 2026 demonstration of the AI-native ODA Canvas, transitioning from an initial proof point into a reusable industry reference environment. This phase focuses on standardizing the onboarding, governance, lifecycle management and observability of agents, tools, models and data products, enabling TM Forum Members to adopt and validate AI-native capabilities through a common, repeatable foundation.

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Participants

Deutsche Telekom AG
Ericsson Inc.
Jio Platforms Limited
Vodafone Group
Amazon Web Services, Inc.
Axonect Sdn Bhd
Databricks
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Visit the project at Innovate Asia, 17-19 November 2026

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Scope and key activities

The AI Native ODA Canvas initiative aims to deliver a standards-aligned, developer-ready foundation for AI native telecom architectures and to demonstrate its value through validated autonomous scenarios.

Standardizing AI-native resources

Define common specifications for agents, tools, models, data products and data resources to support consistent onboarding, discovery, governance and lifecycle management across the AI-native ODA canvas.

Enabling trusted operations

Establish reusable governance, access control, policy enforcement and observability patterns to help members operate AI-native capabilities with greater transparency, security and control.

Delivering a reusable reference foundation

Provide a repeatable AI-native ODA canvas reference implementation with reusable operators, CRDs, deployment patterns and integration assets that can support future Innovation Hub and Catalyst initiatives.

Objectives and outcomes

1

Defining common standards

Establish shared specifications for agents, tools, models, data products and supporting resources.

2

Building trusted foundations

Develop governance, access control and lifecycle management patterns for AI-native operations.

3

Enabling operational visibility

Introducing observability and traceability patterns to support transparent and controlled AI-native environments.

4

Validating reusable implementation

Demonstrating a repeatable AI-native ODA canvas reference implementation aligned to industry needs.

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