Chinese AI video model Kling.ai, from parent company Kuaishou, is generating $20M monthly revenue on 12M users. This provides a rare public market comparable for valuing private competitors like OpenAI's Sora, as incumbents like Google don't disclose such metrics for their own models.
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Tech giants like Google and Meta are positioned to offer their premium AI models for free, leveraging their massive ad-based business models. This strategy aims to cut off OpenAI's primary revenue stream from $20/month subscriptions. For incumbents, subsidizing AI is a strategic play to acquire users and boost market capitalization.
OpenAI's revenue projection of growing from $10 billion to $100 billion in three years is historically unprecedented. For comparison, it took established tech giants like NVIDIA, Meta, and Google between six to ten years to achieve the same growth milestone, highlighting the extreme velocity expected in the AI market.
Internal projections reveal ads are a core long-term strategy, not an experiment. OpenAI expects "free user monetization" to generate $110 billion through 2030, with average revenue per user (ARPU) growing from $2 to $15. Gross margins are targeted at 80-85%, mirroring Meta's highly profitable ad business.
Despite concerns about an AI bubble, today's valuations are more grounded than those of the dot-com era. OpenAI's $500B valuation equates to about $650 per active user, which is below the ~$700 per monthly visitor valuation Yahoo commanded in 1999. This suggests today's metrics, while imperfect, are less speculative than the historical "eyeballs" standard.
Chinese AI leaders like Moonshot have lower valuations than US peers because they are often open-source. Unlike closed-source models (ChatGPT, Claude) that capture 100% of the value, open-source projects hope to capture just 10-20% through hosted services, leading to a "missing zero" in their funding rounds.
While competitors focus on subscription models for their AI tools, Google's primary strategy is to leverage its core advertising business. By integrating sponsored results into its AI-powered search summaries, Google is the first to turn on an ad-based revenue model for generative AI at scale, posing a significant threat to subscription-reliant players like OpenAI.
Proficiency with AI video generators is a strategic business advantage, not just a content skill. Like early mastery of YouTube or Instagram, it creates a defensible distribution channel by allowing individuals and startups to own audience attention, which is an unfair advantage in the market.
AI conversations capture high-intent moments, allowing ads to target active decision-making rather than passive attention-grabbing like social media. This fundamental difference could lead to significantly higher average revenue per user (ARPU), making social media's ad performance a floor, not a ceiling for AI platforms.
Contrary to common belief, the earliest AI startups often command higher relative valuations than established growth-stage AI companies, whose revenue multiples are becoming more rational and comparable to public market comps.
Despite an impressive $13B ARR, OpenAI is burning roughly $20B annually. To break even, the company must achieve a revenue-per-user rate comparable to Google's mature ad business. This starkly illustrates the immense scale of OpenAI's monetization challenge and the capital-intensive nature of its strategy.
