OpenAI just crossed 1 million paying business customers, cementing its position as the fastest-growing enterprise AI platform in history. ChatGPT for Work sits at 7 million seats—up 40% in two months. ChatGPT Enterprise subscriptions grew 9x year-over-year. These aren't vanity metrics. They're proof of genuine enterprise adoption at a scale no competitor has matched.
Sam Altman is celebrating by doubling down on his preferred regulatory philosophy: let the market decide, not governments. It's a convenient position when you're winning. It's also dangerously incomplete. Because markets reward growth and efficiency—not safety, equity, or long-term societal stability. And the idea that corporate customers will somehow self-regulate a technology this powerful is either naive or disingenuous. Probably both.
Let's give credit where it's due. One million enterprise customers in roughly three years is unprecedented. For context, Salesforce took 13 years to reach 100,000 customers. Slack took seven years to hit 750,000. OpenAI blew past both by leveraging 800 million weekly ChatGPT users as a built-in distribution channel. That's the real genius of their go-to-market strategy: consumer adoption created enterprise demand, not the other way around. Employees started using ChatGPT at home, brought it to work, IT departments panicked about data security, and OpenAI swooped in with ChatGPT for Work and ChatGPT Enterprise as the "safe" alternative. It's a textbook bottom-up enterprise playbook, executed with surgical precision.
The 40% growth in ChatGPT for Work seats over two months suggests that adoption isn't slowing—it's accelerating. According to McKinsey's latest research on enterprise AI adoption, organizations that have deployed generative AI tools report productivity gains of 15–30% in specific use cases like code generation, content drafting, and data analysis. Those gains create internal champions who push for broader deployment, creating a flywheel effect. OpenAI is riding that flywheel better than anyone. The 9x year-over-year growth in Enterprise subscriptions—aimed at larger organizations with stricter compliance requirements—shows they're not just capturing startups and SMBs. They're winning Fortune 500 accounts.
Here's where Altman's victory lap turns problematic. In multiple interviews and public statements, he's argued that market forces, not government regulation, should determine AI's trajectory. The logic goes: customers will choose safe, ethical AI providers, rewarding responsible actors and punishing bad actors through purchasing decisions. It's a libertarian fantasy that ignores centuries of evidence showing that markets optimize for profit, not public good. Markets gave us leaded gasoline, tobacco advertising to children, subprime mortgages, and opioid over-prescription. In each case, companies maximized revenue while externalizing harm onto society. Government regulation—imperfect, slow, politically compromised—eventually stepped in to correct market failures. AI will be no different.
Altman's position is especially rich given OpenAI's aggressive lobbying for specific types of regulation—namely, rules that favor incumbents and create barriers to entry for competitors. The company has consistently pushed for licensing regimes, government oversight of model training, and safety certifications that would be prohibitively expensive for smaller players. That's not "letting the market decide." That's regulatory capture disguised as responsibility. Stanford's HAI report on AI governance documents how major AI companies are simultaneously arguing against consumer protection regulations while lobbying for technical requirements that consolidate their market position. OpenAI is Exhibit A.
The million-customer milestone tells us that businesses trust OpenAI enough to buy subscriptions. It doesn't tell us they're using the technology safely, equitably, or sustainably. We've worked with dozens of organizations deploying ChatGPT Enterprise, and the reality is messier than the press releases suggest. Most companies have no coherent AI governance framework. They're not auditing outputs for bias. They're not tracking how automated decision-making affects customers. They're not stress-testing for edge cases or adversarial inputs. They're just... using it. Because it's fast, cheap, and their competitors are doing the same thing.
According to PwC's 2024 AI Risk and Governance Survey, 68% of organizations deploying generative AI lack formal policies for responsible use, and 53% admit they don't have adequate tools to monitor AI-generated outputs for quality or safety. That's the dirty secret behind OpenAI's growth: enterprise adoption is outpacing enterprise preparedness. Companies are deploying powerful tools they don't fully understand, in contexts where failure can cause real harm—customer service, hiring decisions, content moderation, financial analysis. The market isn't regulating this. The market is ignoring it in favor of speed and cost savings.
If you're a marketing leader evaluating whether to deploy ChatGPT Enterprise, the answer isn't "yes" or "no"—it's "yes, but with guardrails." The productivity gains are real. The risks are also real. The smart move is to adopt aggressively in low-stakes use cases—content ideation, data summarization, internal documentation—while moving cautiously in high-stakes areas like customer-facing communications, brand positioning, and performance marketing where errors can be costly. We've seen teams get burned by deploying ChatGPT for social media management without human review, only to have the AI generate tone-deaf or factually incorrect content that damages brand reputation. The tool is powerful. It's not infallible.
Build internal governance before you scale. That means defining use cases where AI is permitted versus prohibited, establishing output review protocols, training teams on prompt engineering and quality control, and tracking performance metrics beyond just efficiency. If you're seeing 30% productivity gains but generating content that underperforms by 15% on engagement, you haven't gained anything—you've just automated mediocrity. The million-customer milestone proves that OpenAI has won the adoption race. It doesn't prove that those million customers are using the technology well.
Sam Altman wants the benefits of market dominance without the responsibilities of regulatory oversight. He wants customers to trust OpenAI's safety commitments while fighting against independent audits and transparency requirements. He wants governments to stay out of AI governance while simultaneously lobbying for rules that advantage incumbents. You can't have it both ways. Either markets are sufficient to regulate AI—in which case, OpenAI should welcome competition, open access, and zero government intervention—or markets need guardrails, in which case, stop pretending regulation is unnecessary.
The million-customer milestone is genuinely impressive. It proves that OpenAI built something businesses want. But growth doesn't equal responsibility. Scale doesn't equal safety. And market success doesn't absolve a company from accountability. Bill Gates was right to warn Satya Nadella about burning billions. The market hasn't decided whether OpenAI's economics work—Microsoft's checkbook has. And the market hasn't decided whether AI deployment is safe—it's just decided that it's profitable. Those are very different things.
Ready to deploy AI responsibly—with guardrails that protect your brand and compliance that scales with your adoption? Winsome Marketing's growth experts help teams build AI governance frameworks that balance speed with safety. Let's talk.