Can OpenAI Really Master Advertising? Brian O'Kelley and Industry Experts Raise Questions on Multi-Front Strategy

OpenAI stands at a critical crossroads. The company that promised never to turn to ads is now embracing them as a lifeline. But as the San Francisco-based AI leader scrambles to unlock new revenue streams, a fundamental question looms: can any company effectively pursue so many ambitious goals simultaneously?

The financial reality is stark. OpenAI generated approximately $13 billion in revenue last year, yet faces the prospect of investing $100 billion over the next four years to maintain its computational edge. The disparity is staggering, and the pressure is intensifying. While founder Sam Altman once declared that “advertising is the last resort for us as a business model,” this week the company began rolling out paid content in ChatGPT—a pivot that underscores how dramatically circumstances have shifted.

The $100 Billion Problem: Revenue Needs Meet Business Model Challenges

Last year, approximately 60% of OpenAI’s revenue came from consumer products, with 40% flowing from enterprise technology. Most consumer income depends on subscriptions: among ChatGPT’s 800 million users, only about 6% pay at least $20 monthly for premium access. This narrow revenue base cannot sustain OpenAI’s ambitions.

The company hopes to triple revenue this year alone. To do so, it must expand into unfamiliar territory on multiple fronts—a strategy that carries considerable risk. “OpenAI is trying to win over consumers, catch up with Anthropic’s programming tools, build data centers, and keep fundraising all at once. There’s just too much it’s chasing,” according to Brian O’Kelley, CEO of advertising platform Scope3 and a 20-year veteran of the industry. “Can it really do advertising well? Can it really do everything it wants to do well?” His skepticism reflects a broader concern among business strategists about companies attempting simultaneous transformations.

Why Advertising Despite Past Objections

Two years ago, at an event at Harvard University, Altman explicitly opposed placing ads in ChatGPT, warning that such a move would erode user trust in the flagship product. Yet the calculation has changed. With enterprise customers and subscription revenue insufficient to close the gap, advertising represents one of several experiments aimed at capturing incremental profit.

The challenge is formidable. OpenAI has no true advertising pedigree. The company recently began assembling an ad sales team, but this initiative remains in its nascent stages. According to Mark Zagorski, CEO of advertising verification firm DoubleVerify, “OpenAI doesn’t really have a true sales team. They need to build the infrastructure and technical systems required to operate an ad business.”

To accelerate this effort, Altman recruited Fidji Simo in May, a former Facebook executive who previously served as CEO of Instacart, where she championed a shift toward an ad-centric business model. Following her appointment, OpenAI poached hundreds of employees from X and Meta, many with backgrounds in advertising products. Yet even with fresh talent, success is uncertain. Zagorski likened the situation to Netflix’s entry into advertising—a process that consumed two years and required outsourcing most of the heavy lifting to specialized firms with deeper expertise.

Enterprise Strategy Faces Mounting Competition From Anthropic

Simultaneously, OpenAI aims to increase enterprise revenue from 40% to approximately 50% by year-end. This represents the key battleground that technology investors are monitoring closely, according to UBS analyst Karl Keirstead. “OpenAI has no choice but to push more aggressively into the enterprise software market,” he noted, highlighting the stakes for the company’s long-term profitability.

Enterprises currently purchase tools like Codex, which assists developers in writing code, and ChatGPT Enterprise. Silicon Valley tech professionals extensively employ these products, with some paying up to $200 per month. However, mainstream businesses may balk at such pricing for office software. More critically, OpenAI faces intensifying competition from Anthropic and its code generation solution, ClaudeCode.

Anthropic has deliberately positioned itself as the enterprise-focused alternative. The strategy became evident when the company aired a Super Bowl advertisement, playfully critiquing OpenAI’s ad ambitions with the message: “The age of AI ads has arrived—but Claude has no ads.” Altman responded on X: “Anthropic sells expensive products to rich people. We’re glad they do that; we do it too, but we also strongly believe we need to bring AI to the billions who can’t afford a subscription.”

New Frontiers: Value Sharing and the Prism Initiative

OpenAI is also experimenting with unconventional business models that could attract or alienate customers. At last month’s World Economic Forum gathering in Davos, CFO Sarah Friar introduced a concept called “value sharing.” The idea suggests that if OpenAI’s technology contributes to significant breakthroughs—such as pharmaceutical discoveries—the company might participate in resulting profits.

Shortly after, OpenAI unveiled Prism, a product aimed at scientists. The announcement triggered immediate concern. Many researchers interpreted Friar’s remarks as signaling that OpenAI would claim a percentage of scientific discoveries enabled by the platform. Alarmed by potential backlash and customer defection, company leadership convened to address the public furor.

Kevin Weil, recently appointed as OpenAI’s Chief Science Officer, clarified on social media that the company would not extract a fee from individual researchers using Prism. Other executives reinforced this stance on X. Weil, however, did not foreclose the possibility of partnership agreements with large pharmaceutical firms in which OpenAI might share financial gains.

During a Silicon Valley event this week, Altman articulated a similar sentiment: “We may explore some partnership models where we bear the costs and share in the proceeds.” This measured language suggests OpenAI intends to pursue selective collaborations while maintaining distance from individual scientists—an attempt to navigate the tension between profit ambitions and user relationships.

The Strategic Balancing Act: Can OpenAI Execute?

As Brian O’Kelley and other industry observers have noted, OpenAI is attempting an extraordinarily complex feat: simultaneously building consumer engagement through advertising, capturing enterprise clients amid fierce competition, launching experimental products, managing fundraising imperatives, and constructing the infrastructure to support its growth. The precedents are cautionary. Netflix required years to achieve profitability in advertising. Google’s dominance in ads rests on decades of accumulated expertise and network effects.

OpenAI’s path forward hinges on whether disciplined execution across multiple domains is feasible. The next 12 months will prove instrumental in determining whether the company can establish itself as a serious contender in advertising, lock in enterprise customers, and stabilize its financial trajectory—or whether the pull in too many directions will ultimately constrain its impact in any single arena.