Telecom operators are accelerating their migration to cloud-native infrastructures to enable automation through artificial intelligence.
Research from Omdia forecasts global spending on cloud technologies and software for telecommunications networks to rise from $17.4 billion in 2025 to $24.8 billion by 2030, reflecting a compound annual growth rate of 7.3 percent. This sustained investment signals a significant transformation of network infrastructure across the industry.
For business leaders, these figures illustrate the realities and opportunities of moving away from legacy systems toward more flexible, AI-ready cloud platforms. Omdia expects growth to accelerate in 2025 by about 12 percent—roughly double the pace seen in 2024—driven by improved cloud management tools, automation frameworks, and the increasing use of AI for network operations.
The strategic benefit for service providers is improved operational efficiency and greater agility in delivering services. By adopting software-defined, cloud-based platforms, telecom companies can apply AI to automate network provisioning, scaling, and lifecycle management. These capabilities are critical to monetizing new services and meeting the performance requirements of 5G and edge computing.
AI has become central to this transition. Omdia notes that more than 62 percent of organizations now regard AI as a decisive factor when selecting cloud infrastructure. Telecom operators are deploying on-premises AI solutions from vendors such as NVIDIA, Red Hat, and VMware to optimize network performance, predict maintenance needs, and detect fraud. This mirrors broader industry trends where enterprises use managed AI offerings—such as cloud-based model platforms—to build and scale AI-driven applications.
However, the shift brings operational and integration challenges. A major challenge is migrating from legacy virtual network functions (VNFs) to cloud-native, container-based network functions (CNFs) without disrupting existing services or creating security and compliance gaps.
Inderpreet Kaur, Senior Analyst at Omdia, highlights that telecom operators are rapidly modernizing their infrastructure to support cloud-native network functions and AI-driven automation, and that migration requires careful planning and balance.
“Telcos are rapidly modernising their infrastructure to support cloud-native network functions and AI-driven automation,” Kaur says. “The migration to CNFs is encouraging telcos to focus their investments on platforms that support both VNFs and CNFs.”
Spending patterns reflect this pivot: investments in Kubernetes-based platforms are projected to grow rapidly—around 25 percent annually—while investment in traditional VM-only architectures is tapering. Although many network functions will remain on-premises for performance and regulatory reasons, use of public cloud for these functions and AI workloads is expected to increase from roughly 3 percent in 2024 to 13 percent by 2030, as major cloud providers introduce more telecom-specific capabilities.
Adopting containers and Kubernetes is not an end in itself; it enables automation that creates measurable business value. Omdia’s research finds that vendors who can automate end-to-end cluster lifecycle management and orchestration provide a clear competitive advantage.
Standardised platforms are also essential for managing hybrid environments that combine VNFs and CNFs. The report identifies Red Hat as a market leader in cloud infrastructure management with about 25 percent market share, underscoring demand for platforms that bridge legacy and cloud-native network functions.
Looking ahead, infrastructure success will be judged by its ability to run AI effectively. The industry focus is shifting from basic virtualization to building a resilient, AI-ready foundation that supports automation and innovation over the next decade.
Technology leaders across industries should take note: preparing for the future requires a move to cloud-based, automated, and AI-capable infrastructure. While the transformation is complex, the performance, agility, and competitive advantages it delivers are increasingly essential.
See also: How Vodafone is tapping AI to automate 5G network operations
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