Moving from AI experimentation to operational execution

AI has been part of the telecom transformation agenda for several years. The conversation is now becoming more practical.

Operators are asking how AI can work with existing OSS and BSS environments, which operational challenges should be addressed first, how AI can be governed responsibly and, most importantly, how it can deliver measurable business outcomes.

Based on conversations with telecom operators, architects, technology leaders and transformation teams at DTW Ignite 2026, this whitepaper discusses  five conversations shaping the next phase of telecom AI adoption.

1. From AI experimentation to operational execution
AI is moving beyond standalone applications towards intelligent capabilities embedded across everyday telecom operations.

2. Governance as a foundation for AI
Responsible AI requires accountability, explainability, data protection and human oversight as AI becomes part of operational decision-making.

3. Connecting the telecom operational landscape
AI needs connected CRM, OSS, BSS, billing, network and operational environments to understand context and support end-to-end decisions.

4. Building trusted data for trusted AI
Reliable, governed and connected operational data is essential for AI-driven recommendations that teams can trust and act upon.

5. Prioritising AI for measurable outcomes
The focus is shifting from deploying more AI use cases to selecting the initiatives that can deliver meaningful operational value and scaling from proven results.

To read the full perspective

Download the complete whitepaper and explore the five priorities shaping the next phase of AI adoption across telecom operations.