Default, GPT-5.5 or Claude for Legal Document Review? A Law Firm's Guide to the Copilot Picker

Law firms use Copilot for the work around the work as much as the law itself. Prepping a matter, reading into a contract, finding the right precedent in the firm’s own files, drafting a first version of a letter that a fee earner will then take apart. Some of that is routine. Some of it is careful reading, where a wrong inference is a real problem.

Microsoft 365 Copilot Chat lets you choose which model handles each request. Most people never open the picker. For legal work that choice deserves more thought than it usually gets, and so does the governance sitting underneath it.

Why model choice matters for careful reading

For routine tasks the default model is fine. A quick summary, a tidy-up of a file note, a first cut of a standard email. The picker earns its keep when the reading has to be careful.

Close contract review, spotting the clause that does not match the rest, reading a long document for what it does not say as much as what it does: these reward a model built for sustained reasoning. As the fuller guide to the Copilot model picker sets out, GPT-5.5 is built for analytical work, and Claude Opus tends to flag where it is uncertain rather than present a confident guess. For legal reading, a model that says this clause is ambiguous, check it, is worth more than one that glosses over it. A smooth, wrong answer is the dangerous kind.

This is not about trusting the model more. It is about trusting it appropriately. A model that surfaces its own doubt gives the reviewing lawyer somewhere to look first, which is the opposite of a tool that buries a bad inference in confident prose. On a long document under time pressure, that signal is worth real money.

Governance comes first

For a law firm the model question cannot be separated from the governance question. Settle this before anyone starts switching models on live matters. This is the part to get right.

Client confidentiality and the tenant. The reason to do this work inside Copilot rather than a public tool is that the matter stays in your governed Microsoft 365 environment. Pasting a client document into a personal ChatGPT or Claude.ai account is the risk to design out. Copilot keeps the work in the tenant, under your controls. Our practical guide to using Copilot with client data goes through this properly.

The distinction is simple to state and easy to forget under deadline. Inside Copilot the matter stays in an environment your firm governs and can audit. In a personal account it does not, and you have lost the ability to say where it went. For a firm that owes a duty of confidence, that difference is the whole point.

The Anthropic approval and hosting nuance. Using Claude inside Copilot is not automatic. Your firm has to approve Anthropic models first, and at present those models run outside Microsoft-managed environments, under Anthropic’s terms rather than inside the Microsoft data boundary. In the UK they are off by default in the admin centre for that reason. This does not make Claude unusable for legal work. It makes it a decision the firm should take deliberately, with the people who own risk in the room, rather than a switch a fee earner flips mid-matter. It is still far safer than the public-tool habit it replaces, because the work stays inside Copilot.

Where human review is non-negotiable. No model output goes to a client, a court or the other side without a qualified human checking it. That holds whichever model produced it. A more capable model gives you a better draft. It does not carry professional responsibility, and it cannot.

Set that expectation early, before anyone gets comfortable. The better the drafts get, the stronger the pull to wave them through, and that is exactly when a missed error does the most damage. The model speeds up the first draft. The final review, the part that protects the client and the firm, stays human.

An SRA-aware mindset. The questions a regulator would ask are the questions to ask yourself. Do you know where the data went. Can you supervise the work. Is there a named human accountable for the output. If you can answer those for every model in the picker, you are on solid ground. If you cannot, the answer is to settle the governance, not to avoid the tool.

None of this is unique to AI. It is the same supervision and confidentiality discipline the firm already applies to a junior’s work or an outsourced task. The model is new. The duties are not, and the firms that frame it that way tend to adopt faster, because the questions already have owners.

Per-job guidance

With the governance settled, the per-task picture is straightforward.

• Routine drafting, summaries and internal notes: the default is fine.
• Close contract review, matter analysis, reading where nuance matters: switch to GPT-5.5 or Claude Opus, with Claude Opus the natural choice where you want flagged uncertainty.
• Anything client-facing, anything filed, anything advised on: switch if it helps, then review it in full. Never rely on any model unchecked.

The shift towards software that acts on its own, not just answers, is already visible in what autonomous agents mean for professional services. The firms that handle the model picker thoughtfully now are the ones that will handle that next step well.

Where to start

Choosing a model is the small decision. Building the judgement and the governance around it is the work.

We help law firms adopt Copilot in a way that respects client confidentiality and the way the firm operates day to day. If you want to settle the governance before you settle the model, book a free consultation and we will start with where your controls stand today.