Citigroup lifts AI market view to over US$4 trillion on enterprise adoption

Citigroup lifts AI market view to over US$4 trillion on enterprise adoption

Citigroup expects the global AI market to reach more than US$4.2 trillion by 2030, with roughly US$1.9 trillion of that tied to enterprise AI.

Citi previously estimated the global AI market to be worth more than US$3.5 trillion, with nearly US$1.2 trillion driven by enterprise AI. (EPA Images pic)
BENGALURU:
Citigroup raised its global artificial intelligence market forecast, citing faster-than-expected enterprise adoption of artificial intelligence tools for coding and automation, with companies such as Anthropic showing strong revenue growth.

The Wall Street brokerage, in an April 27 note, expects the global AI market to reach more than US$4.2 trillion by 2030, with roughly US$1.9 trillion of that tied to enterprise AI.

Citi previously forecast the global AI market to be worth more than US$3.5 trillion, with nearly US$1.2 trillion driven by enterprise AI.

Enterprise demand and revenue are being driven by Claude models and Claude Code, while Mythos represents potential future benefits rather than near-term monetisation.

Anthropic is “the leader in enterprise AI,” due to strong traction in commercial uses such as software development and task‑automating, agentic workflows.

Early and sustained focus on enterprise customers has given the firm a structural advantage, even as it navigates rising compute costs, capacity constraints and intensifying competition from rival AI labs.

About 80% of Anthropic’s revenue comes from enterprise customers, reflecting a deliberate shift away from consumer-first AI strategies.

Anthropic’s annualised revenue run rate has surged past US$30 billion by April, one of the fastest growth trajectories in tech history.

Company has signed major computing‑capacity deals, including up to US$40 billion from Google earlier this week and as much as US$25 billion from Amazon.

Competition is tightening as OpenAI, Google and others push deeper into enterprise markets, shifting the battle toward workflow integration and reliability rather than AI model benchmarks.

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