Which AI chatbot should a law firm buy?
My practical view on ChatGPT, Claude, Copilot, Gemini, and Perplexity for law firm use
By popular request
A managing partner recently asked me: which AI chatbot should his firm buy? He is our happy customer and among the most forward-thinking lawyers I’ve met.
He is not the first senior lawyer to ask me this. White-collar workers all over the world have found AI chatbots useful, and legal work is no exception.
This is my practical view as at May 2026: a starting point, not a permanent ranking, because model quality, usage limits, features, and privacy terms can change quickly.
First, select the right product tier
Before comparing products, there is an important caveat: the relevant distinction is not simply free versus paid.
Some paid tiers are still consumer products, and may not give the firm the no-training commitment, admin controls, access controls, retention controls, and internal usage policy it needs.
The Law Society has already warned lawyers about publicly available AI tools that are not designed for business or enterprise use. I wrote about that recently.
That warning still applies here. If a firm is going to upload privileged, confidential, client, or opposing-counsel documents, it should not do that through unmanaged consumer accounts. It should use business or enterprise AI with the correct legal and operational safeguards, and review whether prompts, uploads, and outputs may be used for model training or service improvement.
This sounds tedious, but it is the price of taking professional obligations seriously.
Powerful, but not simple
AI chatbots are powerful, but not simple.
There are different underlying models, product interfaces, file-handling systems, project workspaces, connectors, memory features, and reasoning modes. Even within the same product, one model may behave differently from another. A newer model may be better at reasoning but worse at style. A faster model may be good enough for many tasks but less reliable for difficult ones.
That is why these tools work best with people who are motivated to experiment.
The user does not need to become a software engineer. But the user does need enough initiative to test different approaches, notice failure modes, and keep asking the tool to improve the answer.
Some lawyers will naturally push the tool hard. Others will try it once, get a bad answer, and give up. If the firm starts with the wrong product, the wrong tier, or the wrong use case, the risk is that people come away thinking AI is not useful, when the real problem was the setup.
Where AI chatbots are good
AI chatbots are strongest when the work is open-ended, ambiguous, and text-heavy.
They are good at reading, summarising, comparing, reorganising, and synthesising large amounts of material. They can help a lawyer test an argument, identify themes, produce a first-pass chronology, compare versions of a document, or work through research across many sources.
That does not mean the answer can be accepted blindly. It cannot. The lawyer still has to check the source material, exercise judgment, and verify the law.
But as a thinking partner for messy text work, the best AI chatbots are already useful.
I know litigators who use these tools to sift through large document sets, identify potentially relevant material, and work out where human attention should go first.
A friend goes further. When opposing counsels serve large document dumps at the last minute, in the name of their Kadar disclosure obligations, he can avoid turning the firm’s associates into an all-hands document review team. He uses AI not just to review the documents, but to help build custom visualisations from them. Those visualisations then help him decide which documents to single out in court during cross-examination.
That is the kind of use case where general AI starts to matter: not because it replaces legal judgment, but because it helps a lawyer find structure in material that would otherwise take far longer to work through.
For ambiguous work with a critically engaged user, these tools can be very good.
Where AI chatbots are weaker
AI chatbots are less convincing when the firm needs a repeatable workflow.
If the task is prescriptive, high-volume, and expected to produce consistent structured output every time, a blank chatbox is often the wrong interface. The user has to know what to ask, how to upload the context, how to constrain the answer, how to check the result, and what to do when the answer is subtly wrong.
That is a lot to ask of every lawyer, paralegal, and secretary in the firm.
This is where specialised legal software should earn its keep. It should absorb the prompting complexity into the workflow: what documents matter, what fields have to be extracted, what source links need to be preserved, what exceptions are common, and what format the lawyer needs at the end.
In other words, AI chatbots are excellent for open-ended thinking. They are less good for complex, repeatable workflows.
ChatGPT Business
ChatGPT Business is my default first recommendation for most law firms.
The model quality is strong, the interface is familiar, file handling is good, and Projects can be used as lightweight matter workspaces. A project can hold instructions, chats, and uploaded files, so the lawyer does not have to start from a blank context every time.
It also tends to be less frustrating for broad daily use because the usage limits are generally more forgiving than Claude’s. That matters if lawyers are asking many follow-up questions, testing, revising, uploading more material, and trying again.
For a controlled pilot, ChatGPT Business is probably the best default starting point.
Claude Team
Claude Team belongs on the same shortlist.
Many lawyers like Claude for reading, summarising, and drafting from long documents. Depending on the exact model, and these models change quickly, some users prefer Claude’s more conversational style and personality.
Claude Projects are also useful because they keep related chats, documents, and instructions together.
Claude also now has a Legal plugin, aimed mainly at in-house counsel use cases such as contract review, NDA triage, compliance workflows, legal briefings, and templated responses. Law firms would still need to test it carefully against their actual work, but it is another reason Claude is worth taking seriously.
The main practical concern is usage limits. Heavy users may hit them more quickly than they expect, especially if they are doing long-document work.
So I would treat ChatGPT and Claude as roughly equal candidates, with ChatGPT probably the better default for broad firm-wide use because of usage headroom.
Microsoft 365 Copilot
I would be careful with Microsoft 365 Copilot.
On paper, it sounds like the obvious choice for many law firms. Most firms already use Microsoft 365. Copilot sits inside Word, Outlook, Teams, and the Microsoft ecosystem. Some firms may also be offered discounts or bundled pricing.
Many of my customers have tried it. The feedback has not been enthusiastic. Several have told me they are much happier using our product than trying to make Copilot do the same work.
That does not surprise me. Microsoft has often won by bundling middling products into software that companies already buy, then relying on distribution. It is not a new strategy. But convenience and bundling are not enough.
Beyond anecdotes, this recent piece has the receipts. The author gave Microsoft Copilot duplicate synthetic datasets that should not have supported meaningful group differences. Copilot nevertheless produced confident cultural explanations from noise.
That is exactly the kind of failure lawyers should worry about: not an obviously ridiculous answer, but a fluent answer that sounds analytical while inventing significance that is not really there. In this case, the same experiment was run on other leading models, and they did not fail in the same way.
But if the question is what I would recommend a law firm start with today, Microsoft 365 Copilot would not be my default.
The stakes are higher than they may seem.
If a firm’s first serious AI rollout is a mediocre tool, that can be worse than no rollout, because it teaches lawyers the wrong lesson: not that Copilot is weak, but that AI is overhyped.
Gemini
Gemini is credible if the firm is already Google Workspace-native.
Compared to ChatGPT and Claude, the perception is that Google Gemini is not as polished but rapidly catching up.
If the firm already works heavily in Google Drive, Gemini and NotebookLM may fit naturally into existing habits. But I would not switch a law firm to Google Workspace just to use Gemini.
Perplexity
Perplexity is useful for research, web search, and current-awareness work, especially where sourced answers about recent developments matter.
But I would treat it as a research add-on, not the firm’s main workspace for privileged matter documents.
If a firm wants to use Perplexity seriously, it should use the enterprise tier and review retention, training, and data-sharing terms carefully.
Beware account sharing
I know firms that reduce cost by buying one paid AI account and letting several lawyers or staff share it. I understand why. Some firms are rightly cost-conscious, especially if they are still testing whether these tools are worth paying for.
But for privileged or confidential legal work, I would be careful. I have written before about why seat-based pricing can create awkward incentives, but account sharing is not the right answer for confidential legal work.
Account sharing means weaker user accountability, weaker matter separation, harder offboarding, poorer auditability, and higher risk that confidential information is exposed to the wrong person.
A better low-cost approach is to buy a small number of seats for a controlled pilot, assign them to specific lawyers or staff, and restrict privileged-document uploads to approved business or enterprise workspaces only.
My practical recommendation
For most law firms, I would start with a controlled pilot of ChatGPT Business and Claude Team.
Give seats to people who are motivated to experiment, and test the tools on real but appropriate work: long-document review, chronology building, research synthesis, drafting, and internal knowledge work.
If the firm is already Google Workspace-native, test Gemini too. Use Perplexity as a research add-on if it fits. I would not lead with Microsoft 365 Copilot just because it is familiar, discounted, or bundled.
The AI wave is just beginning
I have no doubt that AI will transform white-collar work.
I have spoken to lawyers who can already tell when clients are using AI to help write emails. Sometimes that is useful. Sometimes it means the lawyer has to work through a great deal of confident, verbose slop before getting to the actual issue.
That is annoying, but it is also revealing. The wave is already reaching clients, opposing counsel, staff, and lawyers themselves. Law firms that adapt to this wave early will have an edge.
But adopting AI is not just about choosing a chatbot.
Chatbots are the most visible entry point. The deeper change is how legal work will be searched, reviewed, drafted, structured, checked, and managed.
This is why I liked the managing partner’s question. He was not asking whether a generic AI tool should replace the software his firm already uses. He was asking what else his team should have in its toolkit.
That is the right frame.
If a product is just a thin wrapper around a general AI model, it is vulnerable.
But if the product is built around actual legal workflows, jurisdiction-specific practice, firm templates, source-checking, structured outputs, and the way staff really work, then general AI is complementary.
That is the role I want Northbridge Lab to play for our customers. Not pretending every problem needs our software, and not pretending generic AI tools are irrelevant. The point is to partner with law firms to work out what belongs where.
For general AI chatbots, my answer today is simple: start with ChatGPT and Claude.