IPO prep is one of the most document-heavy, deadline-driven, error-prone processes in corporate law. Thousands of pages of filings, disclosures, due diligence materials — all of it needing to be reviewed, cross-checked, and stress-tested before a company rings the opening bell. It’s exactly the kind of work that looks like a perfect fit for AI. And now Cooley LLP, one of Silicon Valley’s most prominent tech-focused law firms, has built something to prove that out. Their tool is called GO Public, built on ChatGPT Work, and according to OpenAI’s case study, it’s already changing how Cooley’s lawyers handle the IPO process — surfacing issues earlier, reducing manual review time, and letting attorneys focus their judgment on the decisions that actually require it.
Why IPO Work Is Such a Painful Target for Automation
To understand why GO Public matters, you have to understand what IPO preparation actually looks like from inside a law firm. The work isn’t just filing an S-1. It involves coordinating across dozens of workstreams simultaneously — auditor sign-offs, SEC comment letters, lock-up agreements, risk factor disclosures, underwriting agreements, and a constant back-and-forth between company counsel, underwriter counsel, accountants, and the client’s internal legal team.
The documents are long. The stakes are high. And the timelines are brutal. Missing an inconsistency between a risk factor and a financial disclosure isn’t just embarrassing — it can delay an offering or, worse, create liability down the road. Lawyers at firms like Cooley are smart enough to catch these things, but catching them requires reading everything, multiple times, under pressure.
That’s the problem GO Public is trying to solve. Not replace lawyers. Not automate the judgment calls. Just make sure the information lawyers need to make good decisions is surfaced faster, more reliably, and earlier in the process than traditional manual review would allow.
This isn’t Cooley’s first experiment with AI — the firm has been one of the more forward-thinking large firms on technology adoption. But GO Public represents something more structured than an internal ChatGPT pilot. It’s a purpose-built workflow tool, designed specifically around the IPO process, not a general-purpose assistant with a legal prompt attached.
What GO Public Actually Does
The tool is built on ChatGPT Work, OpenAI’s enterprise-grade deployment platform, which gives organizations the ability to build custom AI applications on top of ChatGPT’s underlying models while maintaining data privacy controls. We’ve covered how ChatGPT Work connects AI to measurable business outcomes — GO Public is a concrete example of that in action.
Here’s what the tool is actually doing for Cooley’s IPO teams:
- Issue spotting across large document sets: GO Public can ingest and analyze large collections of IPO-related documents, flagging potential inconsistencies, missing disclosures, or areas that typically attract SEC comment letters.
- Earlier risk identification: Rather than discovering problems during late-stage review, the tool helps surface issues at earlier drafts — when fixing them is less expensive and less stressful.
- Cross-document consistency checking: One of the most tedious parts of IPO prep is making sure that numbers, representations, and risk factors are consistent across the S-1, exhibits, and ancillary agreements. GO Public automates a significant portion of that cross-referencing.
- Workflow integration: The tool is designed to fit into Cooley’s existing IPO workflows rather than requiring lawyers to adopt an entirely new process — a practical design choice that likely explains why adoption hasn’t been a struggle.
- Judgment amplification, not replacement: Critically, GO Public is positioned as a tool that helps lawyers focus their attention, not one that makes legal decisions. The AI flags; the lawyer decides.
The framing here is important. Cooley isn’t claiming GO Public eliminates legal work or cuts headcount. They’re claiming it makes experienced lawyers more effective — which, from a business standpoint, means being able to handle more complex matters without proportionally scaling the team, and delivering better outcomes for clients.
The ChatGPT Work Infrastructure Behind It
Building on ChatGPT Work gives Cooley a few specific advantages worth noting. Enterprise data doesn’t feed back into OpenAI’s training data — a non-negotiable requirement for any law firm working with confidential client materials. The platform also provides audit trails and usage analytics, which matter for a firm that needs to demonstrate responsible AI use to clients and regulators.
This is particularly relevant given growing scrutiny of how law firms are using AI. The increasing transparency around AI model behavior is something enterprise legal buyers are paying close attention to, and building on a platform with documented governance controls is a meaningful differentiator from cobbling something together on an API.
What This Means for the Legal Industry and Its Clients
Let’s be direct about who this actually affects and how.
For Cooley’s Clients
Companies going public are already paying enormous legal fees. A typical IPO legal bill from a firm like Cooley can run into the millions of dollars. If GO Public compresses the time lawyers spend on document review and consistency checking, there’s a question of whether those savings get passed to clients or absorbed as margin improvement. Cooley isn’t publishing pricing data on that dynamic, and it would be naive to assume clients automatically benefit. But competitive pressure from other firms building similar tools may eventually force the issue.
What clients do get, more immediately, is potentially better work product — issues caught earlier, fewer surprises during SEC review, and a team that’s spent less time on mechanical review and more time on actual legal strategy.
For Junior Associates
This is where things get more complicated. Document review and consistency checking is traditionally how junior associates at big law firms learn — grinding through S-1 drafts, catching errors, absorbing how deals come together. If GO Public takes over a meaningful portion of that work, the training pipeline for the next generation of capital markets lawyers changes. That’s not necessarily catastrophic, but it’s not a neutral development either.
I wouldn’t be surprised if we start hearing more law firm partners talk about needing to rethink associate development programs over the next few years, as AI handles more of the foundational review work that used to build those skills organically.
For Competing Law Firms
Cooley is ahead, but not alone. Firms like Latham & Watkins, Wilson Sonsini, and Skadden all handle significant IPO volume and are presumably building or evaluating similar tools. The window where GO Public is a genuine competitive differentiator for Cooley is probably two to three years — after that, this kind of AI-assisted IPO workflow will likely be table stakes. The firms that move slower won’t lose clients overnight, but they’ll face harder questions about efficiency and value.
We’ve seen similar dynamics play out in other sectors. As we reported in our look at OpenAI Astra for Law, the billable hour model creates some awkward incentives when AI starts compressing the time required to do legal work. Cooley’s approach — framing AI as a quality improvement tool rather than a speed tool — is probably the smarter positioning for now.
For OpenAI
This case study is part of a clear pattern. OpenAI wants to show that ChatGPT Work delivers real, measurable outcomes in high-stakes professional environments — not just that lawyers are using ChatGPT to draft emails faster. A purpose-built IPO tool from a prestigious firm is a much stronger proof point than generic productivity claims.
Key Takeaways
- Cooley’s GO Public is one of the most concrete examples of AI being integrated into a specific, high-complexity legal workflow rather than used as a general assistant.
- The tool focuses on issue spotting, consistency checking, and early risk identification — areas where AI’s ability to process large documents quickly adds genuine value.
- It’s built on ChatGPT Work, giving Cooley enterprise-grade privacy controls and governance features that are essential for client confidentiality.
- The competitive implication is real: firms that don’t build similar capabilities in the next few years will face legitimate questions about their efficiency versus AI-enabled competitors.
- The associate training pipeline question is underexplored and will likely become a bigger conversation as these tools mature.
Frequently Asked Questions
What is Cooley GO Public?
GO Public is a custom AI tool built by Cooley LLP on OpenAI’s ChatGPT Work platform, designed specifically to assist with the legal work involved in taking a company public. It helps lawyers identify issues, check document consistency, and surface potential problems earlier in the IPO preparation process.
Does GO Public replace lawyers?
No — and Cooley is explicit about this. The tool is designed to handle the mechanical, document-intensive parts of IPO review so that lawyers can focus their time on judgment-heavy decisions. The AI flags issues; attorneys evaluate and act on them.
What is ChatGPT Work?
ChatGPT Work is OpenAI’s enterprise deployment platform that allows organizations to build custom AI applications on top of ChatGPT’s models. It includes data privacy controls, meaning client data isn’t used to train OpenAI’s models — a critical requirement for law firms handling confidential information. You can read more about how ChatGPT Work connects to business value here.
Is this kind of AI adoption common among law firms?
It’s growing quickly but still relatively concentrated among larger, tech-forward firms. Cooley’s profile — heavily focused on venture-backed tech companies and capital markets work — makes it a natural early mover. Broader adoption across mid-size and regional firms is probably still two to four years away from being widespread.
The real test for GO Public, and for legal AI generally, will come over the next market cycle — specifically when the IPO market heats up and deal teams are under the most pressure. That’s when the difference between firms with mature AI tooling and those without it will become genuinely visible. Based on what Cooley has built, they’re in a strong position when that moment arrives.
