Forrester warns OpenAI could become AI’s BlackBerry as it heads to investors

OpenAI may be lining up for Wall Street, but Forrester is already planting a caution flag in front of the CEO suite. In a note published alongside OpenAI's confidential IPO filing, Forrester warns enterprise customers not to get too emotionally attached to the market leader, arguing that “OpenAI could become AI's BlackBerry FIFO (First In, First Out).” In Forrester's framing, the “company that defines a category is often the one most painfully displaced by it.” Translation: the brand that breaks the market can also be the first one the market replaces once the field matures.

The timing matters. Forrester’s warning is paired with OpenAI taking its first formal step toward a public listing. Alongside its confidential SEC filing, OpenAI published a roadmap built around three ambitions: AI systems that can accelerate research, AI that boosts economic growth, and eventually a personal AGI assistant for everyone. Forrester is not focused on those target states. Instead, it asks a blunt fourth question: what happens if OpenAI does not stay on top?

Forrester points to what it calls a “trifecta” of challenges, and the order is telling. First, OpenAI must persuade consumers to use its agents instead of rivals’. Second, it must convince enterprises to build around its technology. Third, it must stay ahead as the industry races toward AGI. In other words, this is not just a product race. It is a distribution race across consumer behavior, enterprise integration, and long-term technical leadership, all at the same time. Any one failure mode can cascade, because the enterprise layer is where spending becomes sticky.

That is why Forrester zeroes in on the enterprise battle, and it does it with a money-flavored metaphor: “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.” In practice, that “dull middle” is the workflow where costs hide and processes accumulate. If an AI agent becomes embedded there, it stops being an app you trial and becomes infrastructure you route around, budget for, and standardize on. The second-order risk Forrester highlights is almost uncomfortable for buyers: “almost no one does” rip it out, even if better options emerge. That is the lock-in problem, and it is exactly the kind of thing an investor-grade platform story can obscure.

So Forrester’s advice is not “don’t buy AI.” It is “don’t overcommit to a single provider.” The firm argues enterprises should “anchor to the capability you need - not the brand that got there first - and keep your switching costs low.” That is a governance and architecture point as much as a procurement point. If you treat your AI stack like a temporary tool, you can swap providers as the market shifts. If you treat it like a strategic system of record before the market stabilizes, you may inherit the very displacement risk Forrester is warning about.

The warning arrives amid another pressure cooker: competition and pricing. The note also references that OpenAI is reportedly weighing cutting prices to fend off growing competition from rivals, including Anthropic. If the AI market is heading toward a price war, enterprise customers have more leverage than they think, but they also face more churn. Prices can drop, bundled offerings can change, and provider roadmaps can pivot. In a price war, contracts signed today can lock in economics tomorrow. That is the practical reason Forrester’s “keep switching costs low” message lands with finance teams, not just tech teams.

Finally, Forrester adds a regulatory and transparency angle that enterprise buyers should actually care about. Public listing means more disclosure, and Forrester notes it could provide customers with something they currently lack: visibility into OpenAI's finances. Once public, OpenAI would be required to disclose far more information about the cost of training and operating its models, giving enterprise buyers a clearer picture of the economics behind the AI systems they increasingly depend on. That is second-order, but it matters. When you understand the cost structure, you understand the incentives behind pricing, packaging, and uptime commitments. It also shapes what procurement teams ask from vendors, and how boards monitor whether a provider is subsidizing growth or building sustainable margins.

Put it all together and Forrester’s argument becomes less about one company’s destiny and more about a pattern executives should recognize. OpenAI can be the category-definer today and still become the cautionary tale tomorrow. The roadmap ambitions OpenAI published alongside its confidential SEC filing point toward expansion, but Forrester is warning that expansion can magnify failure modes: consumer adoption, enterprise embedment, and the AGI race. For peers in similar roles, the stake is clear. If you are buying AI capabilities now, your job is not to bet on a brand. Your job is to design for change, demand visibility, and avoid accidentally turning a promising vendor into an irreversible dependency.