Scaling AI Deployments

Why It Matters

Scaling AI from pilots to production will determine whether telecom operators can unlock new revenue streams and stay competitive in an increasingly automated, data‑driven market.

Key Takeaways

• Telecom operators face AI pilot-to-production gap due to organizational hurdles
• Clean data, programmable infrastructure, and decision integration are essential scaling pillars
• ROI clarity and trust in probabilistic AI remain major adoption challenges
• Talent shortage hampers large‑scale AI rollout across telecom engineering teams
• Blueprinted AI frameworks and upskilling can turn pilots into profitable services

Summary

The panel titled “Scaling AI Deployments” highlighted the telecom sector’s urgent need to move beyond isolated AI pilots and embed artificial intelligence into core operations. Speakers from Amdocs, Deutsche Telekom, Tech Mahindra and Orange argued that while proof‑of‑concepts are easy to launch, the real challenge lies in crossing the production gate—navigating security, regulatory, and ROI approvals.

Key insights included three technical prerequisites: clean data, programmable infrastructure, and AI outputs tied directly to business decisions. Equally critical were organizational factors: clear business cases, trust in probabilistic models, and a cultural shift from tech‑push to value‑push. The discussion repeatedly referenced “proof of concept purgatory” and advocated a “pilot‑to‑production” mindset that measures technical feasibility, environment fit, and measurable business impact.

Notable remarks underscored talent gaps and the need for upskilling. One panelist warned that early pilots succeed because top talent is involved, but scaling to hundreds of use cases falters without broader skill development. Another emphasized an AI blueprint—standardized patterns and non‑negotiable blocks—to align multi‑country operators and accelerate deployment.

The implications are clear: telecoms must institutionalize AI governance, invest in data hygiene, and launch coordinated upskilling programs. Only then can they transform AI experiments into profitable services, maintain competitive relevance, and meet the growing demand for intelligent network automation.

Original Description

Telcos are overwhelmed with AI pilots but lack business transformation execution. Despite numerous AI-based network optimisation, customer service and operations trials, measurable value remains far too low. The industry must transition from experimental AI to production-scale transformation to re-architect network operations and enable profitable new services.

Featuring:

Philippe Ensarguet, VP Cloud & Software Engineering, Orange

Ahmed Hafez, SVP Network Strategy and Data & AI in Networks, Deutsche Telekom

Amol Phadke, Chief Transformation Officer, Tech Mahindra

Ohad Barnoy, Head of GenAI and Data Solutions, Services and Consulting, Amdocs

Broadcast live 19 May 2026

#telecomtv #theainativetelco #ai #ml #automation #dataanalytics #transformation #telco #csp