Omdia Forecasts Global Telecom Network Cloud Market to Reach $24.8 Billion by 2030

Stock News
11/04

The latest report from Omdia, titled "2025 Telecom Network Cloud Market Tracker and Forecast," projects that global spending on telecom network cloud infrastructure and software will grow from $17.4 billion in 2025 to $24.8 billion by 2030, reflecting a compound annual growth rate (CAGR) of 7.3%.

The report highlights a significant acceleration in cloud adoption by communication service providers (CSPs), with growth expected to reach 12% in 2025—double the rate of 2024. This surge is driven by the increasing maturity of cloud-native tools, automation frameworks, and the deep integration of AI and generative AI into network operations.

According to Omdia Senior Analyst Inderpreet Kaur, "Telecom operators are rapidly modernizing their infrastructure to support cloud-native network functions and AI-driven automation." She added, "The shift toward containerized network functions (CNF) is pushing operators to prioritize investments in platforms that support both virtualized and containerized network functions (VNF and CNF)."

Key trends identified in the telecom cloud market include: - **AI Infrastructure**: Over 62% of operators consider AI/ML capabilities a critical factor in their cloud infrastructure decisions. Vendors like NVIDIA, Red Hat, and VMware are developing localized AI solutions tailored for telecom environments. - **Cloud-Native Growth**: Spending on Kubernetes-based platforms is expected to grow at a 25% CAGR, while investments in VM-only environments are slowing. - **Public Cloud Adoption**: Public cloud usage for network workloads is projected to rise from 3% in 2024 to 13% by 2030, as hyperscale cloud providers introduce telecom-specific solutions. - **Vendor Landscape**: Red Hat leads the telecom cloud platform market with a 25% share, as cloud-native transformation aligns closely with operators' automation goals.

Omdia recommends that technology providers targeting this market adopt CI/CD pipelines and GitOps practices to automate the full lifecycle of clusters and network workloads.

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