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Dell’Oro Group Forecasts AI RAN Revenue to Reach $35 Billion by 2030

28th article in the last 90 days, one of 223 articles referencing Dell'Oro Group. Previous coverage: Ericsson Changing of the Guard (Jun 2026).

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Dell’Oro Group projects cumulative AI RAN revenue of $35 billion from 2026 to 2030, with AI RAN expected to help operators adopt virtualization, intelligence, automation, and O-RAN without expanding the overall RAN market.

Market outlook

The June 2026 AI RAN Advanced Research Report estimates AI RAN revenue will total $35 billion over the next five years (2026-2030). The report also states that AI RAN will not expand the overall RAN market during the forecast period.

Analyst position

“Our market assessment and long-term AI RAN position remain unchanged,” said Stefan Pongratz, Vice President at Dell’Oro Group. “AI RAN is already happening and will scale ahead of 6G.”

Pongratz added that AI RAN tools enhance the RAN but are unlikely to expand the overall RAN market, and that “we expect AI RAN to generate little, if any, incremental RAN revenue the end of the forecast period.”

GPU RAN forecast update

The report revises its GPU RAN projections upward, stating that GPU RAN is now expected to be a $1 billion+ market by the end of the forecast period. It frames the forecast around a base-case assumption that AI RAN does not expand the RAN market.

Near-term technology focus

In the near term, the report says the AI RAN market will remain centered on AI-for-RAN, single-purpose deployments, non-GPU architectures, D-RAN, and 5G. It also ties operator adoption to higher use of virtualization, intelligence, and automation within RAN roadmaps.

Supplier and deployment context

The report says incumbent RAN radio and baseband suppliers are positioned for the initial AI RAN phase. It attributes this phase to AI-for-RAN upgrades using existing hardware.

It further notes that, in its regular RAN coverage, the top five RAN suppliers contributed approximately 96% of 2025 RAN revenue.

This Analyst Signals brief reflects a neutral, fact-based summary of the original research note.

Blog post, originally published at delloro.com.

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