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Ropes & Gray is developing a proprietary AI tool with OpenAI to sort and analyze documents for transactional diligence, initially focusing on material commercial contracts. The system produces summaries and draft reports, but lawyers review its groupings, summaries and source documents before work reaches clients.
Ropes & Gray is developing a proprietary AI tool with OpenAI to make an initial pass through documents used in transactional diligence, beginning with material commercial contracts. The tool sorts and groups records, prepares summaries and drafts a report in the firm’s format, while lawyers remain responsible for checking the analysis before delivering advice to clients.
The tool is designed for a part of deal work that can involve thousands of pages of documents reviewed on tight deadlines. It inventories and categorizes a data room, then groups related documents according to themes and issues. The workflow is intended to examine relationships across a set of records, rather than treat each contract as an isolated file, and to produce both interim summaries and a draft diligence report.
Ropes & Gray says its initial development has focused on material commercial contracts. Lawyers tested outputs against reports written by attorneys for completed transactions, using those comparisons to refine the review rubric and report format. The firm describes the tool’s process as following a consistent framework modeled on steps its lawyers take, from document review through summaries and higher-level analysis.
The system is intended to provide a first pass comparable to work by a capable junior-to-mid-level associate, according to the source report. That characterization is the firm’s assessment, not an independently reported performance measure. Lawyers can inspect the tool’s categorization and interim work and must review source documents before anything is delivered to a client.
How the Tool Could Change Deal Reviews
Transactional diligence can shape how a buyer understands a company’s contracts, risks and potential liabilities before completing an acquisition. A system that organizes large document sets and drafts initial findings could change how legal teams allocate time under compressed deal schedules. If it works as intended, lawyers may spend less time on repetitive document sorting and more on checking evidence, weighing risks and advising clients.
The stated aim is not to replace legal judgment. Human review remains part of the workflow, and the firm says lawyers must be able to stand behind all work sent to clients. That safeguard matters because a missed clause, incorrect grouping or incomplete summary could affect a buyer’s understanding of a transaction. The report does not provide independent accuracy results or a quantified account of time saved, so the practical impact cannot yet be measured from the information available.
For clients, the potential benefit is faster access to organized findings and legal analysis. The source report also frames the effort as a way to make expertise available across more client work. Whether that results in lower costs, quicker decisions or different staffing on deals has not been specified.
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From Document Review to Firmwide Knowledge
In a typical acquisition process, a buyer investigates a seller’s legal and financial claims before finalizing the deal. That review can require lawyers to examine a large data room, identify relevant agreements and assess the implications of their terms. The work is often time-sensitive, particularly when a buyer is preparing a bid.
Ropes & Gray describes itself as an early adopter of AI in the legal industry. Its current collaboration with OpenAI focuses on a particular workflow: commercial contract diligence. The source report says the firm has publicly described an ambition for the tool to produce a detailed, issue-level diligence report in hours rather than weeks. That is presented as an ambition, not as a verified result or a published service commitment.
The firm’s stated next area of interest is broader access to internal knowledge. Howard Glazer, the firm’s partner and head of practice AI, said the firm sees potential in making knowledge from client meetings and prior projects more accessible across its lawyers. The report gives the firm’s size as 340 partners and 1,500 lawyers, but does not describe a deployed system for searching or sharing that knowledge.
“AI is really one of the key ways—if not the only way—to make sure you can maintain the same quality and consistency of advice while moving at a faster pace.”
— Josh Lichtenstein, partner and head of the ERISA Fiduciary Practice at Ropes & Gray
Accuracy, Adoption and Costs Remain Open
The source report does not state when the tool will be available for routine use, how many deals have been tested, or how it performs against specific accuracy measures. It also gives no independently verified figures for review time, staffing changes, cost savings or errors detected. The comparison with junior-to-mid-level associate work is the firm’s description of the tool’s intended or observed capability, without published evaluation details.
It is also unclear how the system handles unusual contract terms, incomplete data rooms or conflicting information across documents. The report says lawyers can inspect the work and source records, but does not detail technical safeguards, data-retention arrangements or how client information is handled. Those details should not be inferred from the existence of the OpenAI partnership.
The source mentions GPT-6 Astra alongside the firm’s proprietary tool but does not explain its role in the diligence workflow or provide technical specifications. It is not clear whether the named model is in production, part of testing or associated with another use. The scope of any future firmwide knowledge system is also not established.
Further Testing and Broader Knowledge Access
Based on the source report, the immediate development path is continued comparison of AI-generated drafts with lawyer-authored diligence reports, followed by refinements to the rubric and report format. Lawyers are expected to keep checking summaries and underlying documents as the tool is developed and used. The report does not announce a public launch date or a timetable for expanding beyond commercial contract diligence.
Glazer has described a possible next phase focused on making knowledge from client meetings and past projects more accessible throughout the firm. That remains a forward-looking ambition rather than a confirmed deployment. Further details about its scope, technical design, safeguards and availability have not been provided.
For now, the key milestone to watch is whether the firm reports measurable results from the diligence workflow, including accuracy, turnaround time and how often lawyers need to correct or supplement drafts. Until those details are available, the tool’s practical impact on deal advice and client costs remains uncertain.
Key Questions
What is Ropes & Gray developing?
A proprietary AI tool developed with OpenAI to make an initial pass through transactional diligence documents, initially focusing on material commercial contracts. It organizes records, groups related documents and drafts summaries and a report in the firm’s format.
Will the AI make legal decisions or replace lawyers?
The source describes the tool as an aid for the first stage of review. Ropes & Gray says lawyers review the interim work and source documents and remain responsible for client-facing advice. The report does not say that the system makes final legal decisions.
Has the firm shown that the tool saves time or money?
The report describes a goal of producing detailed diligence reports in hours rather than weeks, but does not provide measured results or independent evidence of savings. The time and cost impact therefore remains unverified.
When will the tool be available?
No launch date is given in the source report. It describes development and testing, including comparisons with reports from completed deals, but does not set a public release timetable.
What does the firm say it may develop next?
Howard Glazer described a longer-term interest in using AI to make knowledge from client meetings and past projects more accessible across the firm. The report does not announce that such a system has been built or deployed.
Source: openai.com
