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The story behind the story

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Midjourney CEO David Holz says the company's revenue “significantly surpassed” $200M in 2023, and has “gone up” since then, despite its declining web traffic

Over much of the past year, David Holz, the 37-year-old founder of Midjourney, has devoted himself to a single task …

The Information Jemima McEvoy

Context & Ripple Effects

Midjourney's disclosure supplies a rare revenue benchmark for a consumer-facing AI creator tool: reported sales have continued to rise even as web traffic falls. That makes usage metrics alone a poor proxy for commercial traction.

The result contrasts with Cohere's revenue pace coming in far below an earlier projection, underscoring how unevenly AI companies are converting demand into recurring revenue. Midjourney's move into video, where tasks cost materially more than image generation, also gives it a higher-priced workload to sell.

First-order effects

  • Midjourney can point to sustained revenue growth as evidence that its subscriber and task-based monetization is holding up despite weaker top-of-funnel web traffic.
  • Higher-priced video generation creates an immediate path to raise revenue per active customer, while also making the economics of compute-intensive usage more consequential.

Second-order effects

  • Competing AI creative tools face greater pressure to show paid-user depth and revenue per workload rather than cite traffic or broad adoption alone.
  • Customers may see more differentiated pricing by generation type as providers try to align expensive video workloads with the revenue they produce.

Third-order effects

  • If this pattern persists, AI creative software will be valued less like an audience business and more on the durability of paid workflows and AI unit economics.
  • The gap between traffic and revenue could widen as a smaller base of paying professional users accounts for a larger share of demand, though the disclosure does not establish profitability.

The trend: Generative-AI products are shifting from attention-led adoption metrics toward monetization and compute-efficient paid workloads as the more meaningful commercial test.