TL;DR
- Pricing Shift: OpenAI plans to charge advertisers per click for ChatGPT ads, moving away from impression-based pricing to compete directly with Google and Meta.
- Revenue Ambitions: The company targets $102 billion in annual ad revenue by 2030, but its ads manager still lacks conversion tracking and demographic targeting.
- Industry Skepticism: Analysts warn that OpenAI cannot reach its targets without serving millions of small businesses, and early advertisers have struggled to prove results.
OpenAI is planning to charge advertisers per click rather than per impression for ChatGPT ads, a report published on April 15 by The Information revealed, a shift that would put it in direct competition with Google and Meta for performance ad budgets.
According to an agency executive who spoke with OpenAI employees, the company is also exploring action-based ad formats designed to drive specific outcomes like purchases or app downloads. OpenAI has not officially confirmed the CPC pricing plans.
According to leaked internal projections, the company projects advertising will represent 36% of total revenue by 2030. Internal documents target $102 billion in ad revenue from $300 billion in total revenue, per Digiday. At that scale, the pricing shift signals that advertising has become an urgent revenue pillar rather than a side experiment.
The Financial Stakes
OpenAI projects $2.5 billion in ad revenue for 2026, and its ad pilot has already topped $100 million in annualized revenue in under two months. Early traction is notable, but the gap between current performance and long-term targets remains vast.
However, reaching $102 billion in annual ad revenue by 2030 would require the kind of exponential growth that few ad platforms have ever achieved. By comparison, Google’s ad business took over a decade to reach similar scale after launching AdWords in 2000, and it did so with a fully built self-serve platform from day one.
Heracles Media analyst Eric Seufert argued that OpenAI cannot reach its $102 billion advertising target “unless it serves the SMB market,” Digiday reported.
Expanding well beyond enterprise accounts to serve millions of small and mid-sized businesses presents an operational challenge that no AI company has attempted at this scale. The company has so far relied on direct sales relationships rather than the automated, low-touch tools that millions of smaller businesses need.
Furthermore, eMarketer principal analyst Nate Elliott quantified the growth problem: “OpenAI would need to grow its ad business approximately 20x faster than Netflix has achieved.”
Mounting losses add further pressure. OpenAI lost $8 billion in 2024, $25 billion in 2025, and $57 billion in 2026.. Advertising revenue, even at the optimistic target for 2026, would offset only a fraction of those costs.
In contrast, impression-based pricing limits OpenAI to brand awareness budgets, which represent a fraction of global digital ad spending. Performance budgets are where the majority of advertiser dollars flow, and unlocking them requires the accountability that click-based and action-based models provide.
Consequently, a successful CPC model could accelerate growth by attracting performance-focused advertisers who currently have no reason to test a platform that offers only impression-based pricing. For brands accustomed to measuring cost-per-acquisition on Google and Meta, click-based pricing is the minimum threshold for serious budget allocation.
An Ads Manager Still Under Construction
Meanwhile, revenue ambitions collide with a platform that currently supports CPM pricing only, with CPC and CPA listed as “coming soon.” Targeting remains limited to keyword and country-level restrictions, with no demographic targeting or audience buying tools available. Reporting offers only impression and click metrics, with no audience size estimates or optimization capabilities.
Notably, conversion tracking, the foundation of any CPC model, is not yet in place.
Beyond pricing and targeting, the platform is missing key ad infrastructure that advertisers expect from mature platforms. User profile-building, measurement attribution, real-time bidding logic, and fraud prevention are all absent. Code in the ads manager suggests conversion tracking is being built into ChatGPT, indicating active development behind the scenes.
Moreover, daily platform updates, A/B testing infrastructure, and feature flags for different user versions are also active, suggesting OpenAI is iterating rapidly even as the public-facing product lags behind competitors.
“Building an ads manager isn’t just a UI problem…Getting all of that to work reliably at scale is non-trivial.”
Shirley Marschall, independent ad tech consultant (via Digiday)
E-commerce analyst Juozas Kaziukenas argued OpenAI is “doing things backwards…especially among smaller advertisers.” Traditionally, ad platforms build self-serve tools and targeting infrastructure before selling performance-based pricing, not after.
OpenAI’s approach inverts that sequence, launching an ads manager with limited capabilities while simultaneously planning to shift to a pricing model that demands sophisticated click-tracking and conversion measurement. Without reliable click attribution, fraud detection, and reporting granularity, advertisers cannot calculate return on ad spend.
Until OpenAI can offer the measurement tools that performance advertisers rely on, CPC pricing alone may not be enough to unlock meaningful budget shifts away from established rivals like Google and Meta.
Competitive Context and What Comes Next
OpenAI’s approach stands in contrast to historical precedent. Google launched AdWords with a self-serve manager simultaneously in 2000, while Meta and Twitter deployed managers years after beginning ad sales. OpenAI’s path more closely resembles the latter, selling ads through direct relationships with large brands before building the automated tools that smaller advertisers need.
TAU founder Robert Webster observed that “OpenAI is closer to Meta’s starting position than Google’s.”
Building on this trajectory, OpenAI is also extending its ad pilot beyond its initial April deadline, a shift from earlier reports that the pilot would run only through March 2026. Combined with the CPC pricing plans, the extension suggests the company views advertising as permanent infrastructure rather than a limited experiment. W Media Research analyst Karsten Weide described advertising as “an urgent necessity” for OpenAI, reflecting the financial pressure created by billions in projected losses.
Early advertisers have nonetheless struggled to demonstrate results. ChatGPT’s first advertisers could not prove ads work, with click-through rates falling well below Google search benchmarks. OpenAI has since reduced its minimum ad spend to $50,000 to lower the barrier to entry, but the inability to measure conversions remains the central obstacle for performance-oriented brands.
Additionally, ad industry sources noted that the pilot’s initial spend commitments were unusually high for an alpha-stage experiment, further raising the bar for advertisers seeking to justify their participation to internal stakeholders.
Competitive pressure is meanwhile building from both directions. Google delayed its own standalone Gemini chatbot ads to 2026, while Meta is pursuing full AI-driven automation for ad creation and targeting. In this crowded and fast-moving environment, OpenAI’s speed matters as much as its execution. Arriving late with a functional CPC platform could still capture advertiser budgets, but arriving early with a broken one risks lasting credibility damage in an industry built on measurable returns.
OpenAI has pledged that ads will not influence ChatGPT’s answers and that conversations will not be shared with advertisers, commitments that distinguish its approach from the data-driven targeting models of Google and Meta. Already testing ads for Free and Go tier users, the company’s executive Assad Awan outlined a trust framework in March 2026 that prioritizes user trust over advertiser value and revenue, a hierarchy that may constrain the depth of behavioral data available for ad targeting.
Whether that privacy stance can coexist with the granular tracking that performance advertising demands remains an open question. OpenAI has acknowledged that commerce and advertising “are not easy,” and transitioning from experimental impressions to performance-based pricing represents the single largest test of whether the company can build ad infrastructure fast enough to justify its ambitious revenue targets before advertisers lose patience.