OpenAI Files Confidentially for IPO as Forrester Warns Enterprises Against Vendor Lock-In

OpenAI has taken its first formal step toward a public listing, filing confidentially with the US Securities and Exchange Commission, and the move has prompted Forrester to issue a blunt warning to enterprise customers: do not get too attached. In a note published alongside the filing, the analyst firm argued that today's market leader could become tomorrow's cautionary tale, drawing a direct comparison to BlackBerry, the company that defined the smartphone category before being displaced by it.

The advice was specific and operational. "Don't lock into long-term contracts; keep your architectures flexible," Forrester told clients. For anyone responsible for procurement, vendor risk, or compliance, that framing matters more than the IPO headline itself. It reframes the choice of an AI provider as a governance decision with measurable downside, not just a technology preference.

What the SEC filing actually changes

The most concrete consequence of OpenAI's move toward a public listing is disclosure. A confidential filing under the SEC's draft registration process is still an early step, but it puts the company on a path that ends in public financial reporting. Once a company completes a registered IPO, it becomes subject to ongoing obligations under the Securities Exchange Act of 1934, including audited financial statements, periodic reporting on Form 10-K and Form 10-Q, and material event disclosure on Form 8-K.

For enterprise buyers, this is the part of the story with practical value. Forrester noted that a public listing would give customers something they currently lack: visibility into OpenAI's finances. A registered issuer must disclose far more about the cost of training and operating its models, the structure of its revenue, and the risk factors that could threaten its business. Buyers who depend on a vendor's continued solvency gain a documented basis for assessing that risk, rather than relying on private valuations and press reports.

This is worth building into vendor due diligence. When a critical AI supplier becomes a public company, your risk team should plan to read its filings the way it reads any other material vendor's. The risk factors section of a registration statement is, in effect, the vendor telling regulators in writing what could go wrong. That is a resource compliance functions rarely get from a private supplier.

The lock-in problem, stated as a compliance requirement

Forrester's central argument is about switching costs. "Whoever automates the dull, expensive middle of a company's operations first becomes the system of record everyone else has to rip out, and almost no one does," the firm said. The point is that once AI agents are woven into daily business processes, the supplier becomes structurally difficult to replace, regardless of price or performance.

The firm's recommendation translates cleanly into procurement language: "anchor to the capability you need, not the brand that got there first, and keep your switching costs low." In practice, that means a few defensible controls. Avoid exclusivity and long minimum-term commitments where the technology is still moving quickly. Require contractual data portability and exit assistance so that prompts, fine-tuning data, and integration logic are not trapped. Build abstraction layers so that the underlying model can be swapped without re-engineering every downstream process. Maintain a tested alternative provider rather than assuming continuity.

These are the same continuity and concentration-risk principles that regulators already apply to other forms of critical third-party dependence. Financial-sector supervisors have spent years pressing firms on cloud and outsourcing concentration risk, and the logic carries over directly to foundation-model providers. If a single vendor underpins a business-critical process, a regulator examining your operational resilience will reasonably ask what happens if that vendor fails, raises prices sharply, or changes its terms.

A price war raises the stakes

Forrester's warning lands as OpenAI reportedly weighs cutting prices to fend off competition, including from Anthropic, which has filed for its own IPO. A price war is good news for buyers in the short term, but it also signals a volatile market where terms and economics can shift quickly. That volatility is precisely the argument for keeping switching costs low and avoiding contracts that lock in pricing or architecture before the market settles.

Forrester frames OpenAI's challenge as a "trifecta": persuade consumers to choose its agents over rivals', convince enterprises to build around its technology, and stay ahead in the race toward more capable general systems. The enterprise battle is the one with the clearest compliance implications, because it is the one that creates durable dependence. A consumer can switch chatbots in an afternoon. An enterprise that has rebuilt its operational core around one provider's agents cannot.

What to do now

The filing does not require any immediate action from customers, and OpenAI remains the company that helped define the current generative AI era. But the practical takeaways for a risk or compliance function are straightforward. Treat AI provider selection as a concentration-risk decision and document it accordingly. Negotiate exit and portability terms before deployment, not after. Plan to incorporate OpenAI's future public disclosures into ongoing vendor monitoring once they exist. And resist long-term lock-in while the competitive and pricing picture remains unsettled.

Whether OpenAI becomes the next dominant platform or AI's answer to BlackBerry is a question investors will weigh closely. For the teams responsible for governing how their organizations adopt these tools, the more useful question is narrower: if the leading vendor stumbles, can you move? The compliance answer should be yes, and it should be written into the contract.