Contents
Towards Anticipatory AI-Native Telcos
What is an AI-Native Telco?
AI-Native telcos, also known as Anticipatory Techcos, combine AI, data intelligence, and a deep understanding of consumer behavior into their systems to anticipate new opportunities to improve revenue, reduce costs, enhance experiences, and create new business models.
Telco Industry Transformation:
AI-Native’s Push and Pull
Telcos face slow connectivity ARPU growth, higher costs and high customer expectations
1. Global Telecom Outlook FY25—Perspectives Report | PwC (accessed 26th May 2025) | 2. Global Telco Market in 2024: Revenue, Capex, and Profitability Insights for Leading Operators | 3. The Expectation Reset: 7 Ways AI Is Redefining Customer Expectations
Leading telcos that are adopting AI are seeing measurable results:
With many other telcos reporting improved efficiency and customer experiences in 2024:
Top 3 Telco Improvements with AI in 20244
Improved employee productivity
Enhanced customer experiences
Improved network operations
4. NVIDIA - State of AI in Telecommunications: 2025 Trends
Not all telcos are
capturing this value
AI’s Impact on Telco Revenue and Costs 20245
The majority of telcos have not unlocked significant benefits from AI yet.
5. NVIDIA - State of AI in Telecommunications: 2025 Trends
The key problems holding telcos' back from adopting AI include:
Siloed AI Agents
Siloed data: BSS/ OSS, network, channels, etc.
Reactive Mode
AI bolted onto reactive workflows
Operator DIY
High brand and operational risk
AI Management
Cost Center
Cost Center
Long experimentation cycles with unclear ROI
The Reward:
The Anticipatory Techco Flywheel
Successfully adopting AI can put telcos into a virtuous cycle that benefits revenue, cost savings, and new monetization:
Data enriches and enhaces AI
New business models
With deep customer engagement, move beyond telco to unlock new profit pools
Intelligent operations
Delivering a tailored AI-led experience that engages and anticipates customer need
Builds consumer trust and engagement
Provides 360-customer views and insights
Anticipatory experiences
Delivering a tailored AI-led experience that engages and anticipates customer needs
Adopting AI: Bolted-on Incremental AI vs AI-native Approaches
Bolted-on*, incremental AI adoption
risks keeping technical debt issues
AI-native solutions built for
telcos are safer and faster
AI sits on top of
legacy BSS/OSS
Fragmented data leads to insights that lack full context.
No real-time insights
No real-time insights
AI sits on top of
legacy BSS/OSS
Fragmented data leads to insights that lack full context.
No real-time insights
No real-time insights
Increased brand risk
Fewer data protection guardrails, governance, and AI explainability
Reactive:
Harder to anticipate customer demands, need to catch u
AI-native solutions built for
telcos are safer and faster
Full stack software
with AI-as-core
Single source of truth & continuous-learning models built for telcos
Single source of truth & continuous-learning models built for telcos
Faster scaling
Faster pilots: new use cases reuse the same AI foundation
Lower brand risk
Guardrails, governance, & AI explainability built-in
Anticipatory:
Customer-centric AI anticipates needs and creates new value
* Bolted-on refers to adding AI features as an afterthought or separate module to existing systems | 6. TM Forum - How does your GenAI strategy measure up? Key findings from our Generative AI Maturity Interactive Tool
The Role of Full-stack Software in Telco AI Adoption:
A fully integrated solution works from a single source of truth, has built-in automation, and doesn’t need custom integrations. Migrating to a full-stack also solves data readiness issues.
A “Core-to-Edge” Telco Platform Powered by Embedded AI
Redefining telco transformation with the world’s first AI-Digital Mobile Operator (AI-DMO).
Two AI-Native Paths:
Digital Sub-brands and Full-scale Migration
Low Risk Experiments
Full Digital Transformation
Building experimental digital telco sub-brands powered by AI-ready full-stack software
Full-scale migration to AI-native software
1. Start Small:
Launch AI-powered digital sub-brand (AI-DMO)
1. Prep for migration:
Onstage simplification, backstage legacy cleaning & cohort phase preparation
2. Test fast and prove value:
Rapid experimentation with clear KPIs (NPS, ARPU, cos-to-serve)
2. New mobile app migration:
Release of new app with migration of existing customers upon signup
3. Scale confidently:
Apply learnings and shift focus to the AI-DMO
3. Legacy access during migration:
New app can read basic data from legacy stack, providing a seamless UI for old and new
4. Sunset old telco:
(Optional) Retire old telcos to focus on new AI-DMO
4.Controlled migration:
Subscribers can be targeted with new products, triggering a real-time migration
KDDI’s povo sub-brand is powered by Circles full-stack platform
Circles successfully migrated Telkomsel’s 20 million subscribers to our full-stack platform
Low Risk Experiments
Building experimental digital telco sub-brands powered by AI-ready full-stack software
1. Start Small:
Launch AI-powered digital sub-brand (AI-DMO)
2. Test fast and prove value:
Rapid experimentation with clear KPIs (NPS, ARPU, cos-to-serve)
3. Scale confidently:
Apply learnings and shift focus to the AI-DMO
4. Sunset old telco:
(Optional) Retire old telcos to focus on new AI-DMO
KDDI’s povo sub-brand is powered by Circles full-stack platform
Full Digital Transformation
Full-scale migration to AI-native software
1. Prep for migration:
Onstage simplification, backstage legacy cleaning & cohort phase preparation
2. New mobile app migration:
Release of new app with migration of existing customers upon signup
3.Legacy access during migration:
New app can read basic data from legacy stack, providing a seamless UI for old and new
4. Controlled migration:
Subscribers can be targeted with new products, triggering a real-time migration
Circles successfully migrated Telkomsel’s 20 million subscribers to our full-stack platform
Your telco can still catch up to leading AI-native leaders
Leading operators who are improving their revenue, cost savings, and customer experiences are building AI into the core of their systems.
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