Inside OpenAI’s Growth Strategy: 7 Business Lessons Every Entrepreneur Can Learn from CFO Sarah Friar

What OpenAI’s massive investments, evolving business model, and relentless focus on growth reveal about building a company for the future.

Imagine running a business with 800 million weekly active users, billions of dollars in revenue, and demand so overwhelming that you cannot launch your products as quickly as you develop them.

For most entrepreneurs, that sounds like the ultimate success story.

For OpenAI, it's one of its biggest challenges.

At The Wall Street Journal's Tech Live 2025, OpenAI CFO Sarah Friar offered a rare look inside the company's financial strategy, revealing how the artificial intelligence powerhouse thinks about growth, infrastructure, monetization, and the difficult decisions that come with scaling at extraordinary speed.

At the time of the conversation, OpenAI was projecting approximately $13 billion in annual revenue, while simultaneously pursuing enormous investments in computing infrastructure.

The numbers are extraordinary. But behind them are business principles that apply to companies of every size.

Whether you're launching your first venture or working to scale an established business, OpenAI's approach offers seven lessons about building for opportunity, adapting to demand, and creating lasting value.

1. Build for the Market That's Coming, Not Just the One That Exists

One of Friar's most compelling observations was that artificial intelligence is still in its earliest stages.

She compared AI's development to the arrival of electricity.

Imagine a world where electricity had just reached people's homes. The lights worked, and everyone celebrated. But nobody had yet imagined refrigerators, televisions, washing machines, or the countless other innovations electricity would eventually power.

That's how Friar sees AI today.

"We've turned on the lights, but we've not yet thought about how we deploy it."

For entrepreneurs, this illustrates an important distinction between responding to existing demand and recognizing what customers will need next.

The biggest opportunities often emerge when a new technology, behavior, or market shift unlocks possibilities people haven't fully recognized.

Consider your own industry. What technology or changing customer expectation is creating opportunities that established businesses haven't addressed?

The entrepreneurial takeaway: Don't build your entire strategy around today's customer behavior. Study where your market is heading and position your company to serve emerging needs.

2. Your Biggest Growth Constraint Might Be an Opportunity in Disguise

Most founders dream of having more customers than they can handle.

But OpenAI demonstrates that extraordinary demand creates its own challenges.

Friar explained that the company was severely constrained by the computing resources required to operate its AI models.

In fact, she revealed that OpenAI had delayed the release of Sora 2 by approximately six or seven months after the technology was ready.

The problem wasn't a lack of ideas, engineering talent, or consumer interest.

It was infrastructure.

Similarly, Friar explained that certain advanced ChatGPT features were available only to higher-paying subscribers because OpenAI couldn't yet support the computing demands of a wider rollout.

For smaller businesses, this problem might look familiar.

A consulting firm generates more leads than its team can serve. An e-commerce store experiences explosive demand but struggles with fulfillment. A software startup attracts customers faster than its infrastructure can scale.

The lesson isn't simply to grow faster.

It's to identify which bottleneck actually prevents your business from delivering more value.

The entrepreneurial takeaway: Ask yourself: If customer demand doubled tomorrow, what would break first? Your answer may reveal where your next strategic investment belongs.

3. A Simple Business Model Can Become a Powerful Competitive Advantage

When ChatGPT launched, OpenAI didn't begin with an elaborate monetization system.

It started with subscriptions.

According to Friar, that decision was partly influenced by the unexpected speed of ChatGPT's adoption.

Yet what initially appeared to be a straightforward revenue model became a major strategic advantage.

During the interview, Friar described revenue growth from approximately $1 billion two years earlier to $4 billion the previous year, with around $13 billion projected for 2025.

Subscriptions helped establish a foundation before OpenAI expanded into enterprise services, API usage, commerce, and more sophisticated value-based pricing arrangements.

This is particularly relevant to early-stage founders who feel pressure to monetize every possible opportunity immediately.

Too many startups complicate their offerings before establishing product-market fit.

They launch multiple pricing tiers, revenue streams, and complicated partnerships without first proving customers consistently value the core product.

OpenAI's experience offers a different perspective.

Start with a business model customers understand. Demonstrate value. Build sustainable demand. Then explore additional monetization opportunities.

The entrepreneurial takeaway: A clear, repeatable revenue model is often more valuable than five unproven revenue streams.

4. The Best Pricing Strategy Reflects the Value You Create

One of the most interesting aspects of OpenAI's growth strategy is its exploration of pricing beyond traditional software subscriptions.

Friar discussed how enterprise customers increasingly use AI for substantial business outcomes rather than simple productivity improvements.

Consider pharmaceutical research.

If an AI system helps accelerate a complex research process or improves the efficiency of regulatory documentation, its value may be dramatically greater than the cost of generating individual AI responses.

That raises a fundamental pricing question.

Should companies always charge based on how much their product is used, or should they sometimes charge based on the value customers receive?

Friar explained that OpenAI was exploring ways to participate more directly in the value created through specialized enterprise engagements, although some potential models remained under consideration.

For entrepreneurs, this challenges the assumption that pricing must always follow time, usage, or production costs.

A marketing consultant who helps generate significant revenue shouldn't necessarily price solely by hours worked.

A software company that saves customers hundreds of hours could consider pricing around measurable business impact.

The entrepreneurial takeaway: Understand the economic value of the problem you solve. Your pricing should reflect the outcome you help create, not just the effort required to deliver it.

5. Use AI to Improve Decisions, Not Just Eliminate Tasks

When the conversation turned to AI and employment, Friar provided a particularly practical example from OpenAI's finance department.

Traditionally, financial teams spend considerable time investigating budget variances.

An analyst reviews hundreds of financial line items, identifies unexpected changes, and contacts colleagues to understand what happened.

Perhaps marketing spending increased by 300%.

Was it an accounting error? A coding mistake? Or an intentional decision to expand a successful campaign?

Friar explained that OpenAI now uses an AI agent to investigate this process, drawing on internal information to identify potential explanations.

Instead of spending hours gathering facts, the team can focus on more strategic questions.

Did the campaign work? Should the company invest more? Where should resources be allocated next?

The distinction is critical.

Automation shouldn't be measured only by how many hours it saves.

It should also be measured by the quality of thinking and decision-making it enables.

For a small business owner, this could mean using AI to summarize customer feedback, examine sales trends, or prepare financial analyses.

The goal is to free up more time for the decisions that actually move the business forward.

The entrepreneurial takeaway: Don't ask only, "What can AI do for me?" Ask, "What higher-value decisions could I make if AI handled the repetitive work?"

6. Strategic Partnerships Can Unlock Growth You Can't Fund Alone

OpenAI's infrastructure ambitions are staggering.

Friar estimated that building a one-gigawatt data center could require approximately $50 billion, including around $15 billion for land, power, and physical infrastructure and another $35 billion for advanced computing chips.

Clearly, this isn't a challenge a company solves through ordinary operational budgeting.

Instead, OpenAI has developed relationships across its infrastructure ecosystem, including cloud providers, chip manufacturers, investors, and financial institutions.

Friar highlighted OpenAI's AMD warrant arrangement as an example of structuring partnerships around shared financial incentives.

The broader philosophy is straightforward: align partners so that each benefits when the overall venture succeeds.

Early-stage entrepreneurs may never negotiate multibillion-dollar technology agreements, but the underlying principle is highly transferable.

A small product company might collaborate with a distributor instead of immediately building its own sales network.

A startup might partner with a complementary business to reach new customers.

A founder could negotiate revenue-sharing arrangements rather than paying substantial upfront costs.

Partnerships are especially powerful when they help overcome constraints in capital, expertise, distribution, or infrastructure.

The entrepreneurial takeaway: Identify what your business needs to grow but cannot efficiently build alone. Then find partners whose success can be connected to yours.

7. Don't Sacrifice Customer Trust for Short-Term Revenue

Perhaps the most important lesson from Friar's interview concerns monetization and trust.

As OpenAI expands into commerce, it faces a familiar challenge encountered by many technology platforms.

If a company earns money when users purchase products through its platform, does it have an incentive to recommend products that generate revenue instead of products that best serve customers?

Friar was emphatic about the principle OpenAI intends to maintain.

"Not the sponsored answer, but the best possible answer."

She described commerce as an opportunity to help users complete purchases after researching products, rather than a reason to compromise the quality of recommendations.

Of course, maintaining that principle in practice will require ongoing scrutiny as new business models develop.

But the strategic lesson is relevant to every entrepreneur.

Trust is difficult to earn and easy to damage.

A founder who recommends unnecessary services, hides important information, or prioritizes short-term commissions over customer outcomes may generate immediate revenue while weakening the foundation of the business.

The strongest customer relationships are built on confidence that a company will deliver on its promises.

The entrepreneurial takeaway: Before introducing a new revenue stream, ask whether it strengthens or weakens the trust customers place in your business.

The Bigger Lesson: Sustainable Growth Requires Ambition and Discipline

One of the most revealing moments of the conversation came when Friar discussed OpenAI's approach to profitability.

Rather than prioritizing an immediate break-even point, she explained that the company was continuing to invest aggressively because of its growth opportunities.

But that didn't mean ignoring financial discipline.

Friar emphasized the importance of healthy underlying gross margins and understanding whether the core business could support a sustainable financial model.

It's a distinction every founder should understand.

Growth without financial discipline creates vulnerability. Financial discipline without strategic ambition can limit opportunity.

The challenge is knowing when to invest, when to conserve resources, and which opportunities genuinely justify the risk.

OpenAI operates on a scale few entrepreneurs will ever experience. Its financial resources, technological capabilities, and market position are profoundly different from those of an early-stage startup.

But the questions driving its decisions are surprisingly familiar.

Where will demand come from next? What prevents us from growing? How should we charge for the value we deliver? Which partnerships can accelerate our progress? How do we innovate without compromising customer trust?

These are the same questions entrepreneurs face when building their first products, finding customers, and deciding what comes next.

And perhaps that's the most useful insight from Friar's appearance.

Successful entrepreneurship isn't simply about having a bold vision.

It's about continually building the systems, relationships, and business models required to make that vision possible.

For wantrepreneurs ready to become entrepreneurs, that's where the real work begins.