On the heels of the Anthropic filing last week, OpenAI also confidentially filed a draft S-1 with the SEC — its first formal step toward an IPO. On the same day, Sam Altman and chief scientist Jakub Pachocki published a manifesto-style essay, “Built to benefit everyone: our plan.” Last valued at roughly $852 billion, OpenAI hasn’t committed to an IPO timeline, but the pairing is telling. While enterprises generally aren’t immediately impacted by an IPO event of another company, it’s important to understand what these events could mean for AI model companies to inform how tech and business leaders should plan their AI investment approaches in the longer term.
OpenAI must convince both consumers and enterprises to reach for its model-powered agents instead of Google’s, Anthropic’s, or any emerging menu of players — all while still outbuilding everyone on the frontier itself. That’s the trifecta: sticky consumers, automated enterprises, and an artificial general intelligence (AGI) capability lead worth deploying. The proceeds from an IPO could fund a future but only if OpenAI can:
- Create a holistic consumer ecosystem. OpenAI must evolve from standalone capabilities to an integrated consumer ecosystem where agents handle everyday tasks (e.g., travel booking, reporting, etc.) while pulling users into a broader superapp experience. Data from Forrester’s Consumer Benchmark Survey, 2026, shows that 47% of US online adults already use ChatGPT, so usage is widespread. Stickiness won’t come from utility alone — it’ll come from habit, memory, and comfort with apps consumers are already in. That means pairing agents with content, commerce, and community to drive ongoing engagement. A hybrid monetization model (ads + transactions) — similar to Google, Amazon, and Meta — that differentiates beyond search by creating or acquiring compelling content that keeps users in its ecosystem will be key.
- Win enterprise automation. 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. Today, the state of agentic AI indicates that enterprises still lack the orchestration maturity, governance, and ability to handle the complexity required to scale, which means that if OpenAI lands the agents inside real business workflows — where the buying decision runs through security reviews, compliance, and integration — they could help unlock the AI value that enterprises are desperately seeking. If they want to go faster, buying an established enterprise software player is a way to trade years of sales cycles for a customer base that’s already signed.
- Reach AGI. OpenAI believes that AI doing AI research is the path to AGI and that the automated researcher is the engine, AGI is the prize, and each turn makes the next faster. The consumer and enterprise opportunities could fund the journey, but this is the destination that makes the whole IPO make sense. We believe that AGI capabilities will evolve in four stages, offering a more pragmatic lens into why this matters for enterprises.
Enterprises Must Prepare For A Future Without Lock-In
For enterprises tracking how frontier AI companies are shaping their roadmaps, here’s the short version. C-suite leaders shouldn’t slow down: Accelerate AI implementation, especially agentic AI, to stay ahead; don’t lock into long-term contracts; and keep your architectures flexible. In fact, OpenAI could become AI’s BlackBerry FIFO (“first in, first out”). The company that defines a category is often the one most painfully displaced by it, so anchor to the capability you need — not the brand that got there first — and keep your switching costs low. The IPO will make finances transparent, and enterprises will now see how much it costs to train, run, and operate their businesses.
In OpenAI’s essay, it lays out three goals that will define its future. Here’s an explanation of these goals and how they could impact AI’s trajectory in the enterprise:
- Build an automated AI researcher — AI building AI. The first goal is an AI system that can accelerate and increasingly automate the research process itself — all while staying steerable, accountable, and connected to people. The company says that by March 2028, a significant fraction of its own research may be done by AI systems working alongside human researchers — a bet that AI doing AI research will soon set the pace of progress. Our take: When AI agents can write their own “tools” — AKA code — the sky’s the limit. Every frontier model company is racing toward this same approach, which means agents will build their own capabilities on the fly for all enterprise processes.
- Accelerate the economy — early mover advantage. OpenAI’s second goal is to accelerate scientific progress, productivity, and economic growth. The framing leans hard on the idea that everyone should have a meaningful stake in the prosperity AI creates, not just the companies building the systems. Our take: OpenAI stresses “working to ensure the gains are widely shared,” which we believe mostly means shared with whoever moves first. The early movers turn the productivity boost into a lead, and everyone else inherits a more efficient set of competitors.
- Give everyone on Earth a personal AGI — shift from ether to real. The third goal is the most expansive: putting a personal digital assistant (competent AGI) in the hands of every person on Earth to use however they choose. It’s the clearest expression of OpenAI’s distribution-over-concentration thesis — the belief that broadly shared power makes societies more resilient than concentrated power does. Our take: When everyone can have a personal AGI, intelligence stops being a scarce resource. The competitive advantage is lost, and no one needs one. The advantage shifts to what an AGI can’t conjure out of thin air: physical assets, real-world infrastructure, supply chains, energy, and the stuff with a footprint (e.g., SpaceX).
Forrester clients with questions related to this can connect with us through an inquiry or guidance session.
