This post discusses how Databricks is helping telecom operators leverage data and AI to address revenue pressure, high churn, and operational inefficiency, previewing their presence at MWC 2026.
- •Telecom operators face common challenges: declining revenues, high costs, limited personalization, and slow decision-making despite owning vast customer and network data
- •Unified data platforms enable real-time AI decisioning for upsell and next-best-offer, improving attach rates by ~250% and ARPU by ~$8 per customer per month
- •AI models trained on call transcripts and chat interactions reduce churn by approximately 5 percentage points per month while improving agent effectiveness
- •Proactive AI-driven fraud prevention reduces fraud attempts by up to 80% and saves tens of millions annually by shifting from reactive investigation to continuous real-time detection
- •Databricks advocates embedding data intelligence across all operations so networks self-heal, customer channels personalize in r
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