Summary
Cloud and AI Infrastructure
This programme helps telecoms operators, vendors and financial institutions to understand the impact of the transformation of networks and cloud infrastructure into cloud-native, AI-driven digital platforms. It tracks the adoption of the cloud-native networks (5G core, vRAN/Open RAN and public/private/hybrid cloud) and AI infrastructure (GPU and DPU) and services (GPUaaS), their underpinnings (Kubernetes, GitOps and bare metal) and related automation solutions, and the value-chain disruption that they cause.
Topics for 2026
AI-native telco cloud
AI infrastructure evolution
Regional AI infrastructure developments
Highlights from this programme
GPU-as-a-service (GPUaaS): worldwide forecast 2025–2030
Neocloud GPU-as-a-service (GPUaaS) providers: case studies and analysis
GPU-as-a-service (GPUaaS): telecoms operator case studies and analysis
Telecoms AI cloud infrastructure: worldwide forecast 2024–2030
Cloud-native automation and ETSI NFV MANO: evolution, migration and co-existence strategies
Network cloud infrastructure: worldwide forecast 2024–2030
Typical client enquiries
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How will the demand for GPU-optimised data-centre and cloud infrastructure evolve with AI? What is the role and opportunity for telecoms operators?
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How do neoclouds and telecoms operators stack up against hyperscalers in GPUaaS?
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How will sovereignty and geopolitics affect AI infrastructure landscape and investments?
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What is the status of cloud-native network transformation? What are the key drivers and challenges?
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How are operators adopting new operating models and automation approaches for cloud-native networks?
Tag: Practice areas > Research > Networks and Cloud > Cloud and AI Infrastructure