There is now a great deal of discussion about AI in legal practice, and particularly in litigation. Most of it focuses on speed: faster research, faster drafting, faster document review. That is all true, up to a point. AI can help litigators move more quickly across a range of tasks, and those efficiencies are real.
But speed is not the real story. The more interesting development is that AI is changing what good legal work actually looks like.
The question is no longer whether a lawyer uses AI. Increasingly, many will. The question that matters is whether they can use it with enough rigour for litigation work; whether they can verify what it produces rather than simply accepting it. That is where the professional distinction now lies.
Judgment, not output
Litigation has never been about producing words on a page. It is about knowing which facts matter, which authorities genuinely support a proposition, which arguments will survive scrutiny, and which drafting choices introduce avoidable risk. AI can assist with some of that process. It cannot replace the lawyer’s responsibility for any of it.
In practice, this means the most useful lawyers will not be those who know how to prompt a model. They will be the ones who know how to interrogate its output. A good litigator working with AI ought to be asking: where did this proposition come from? Is this authority real, and has it been appealed, overturned, or distinguished? Does this quotation say what the model claims it says? Is the procedural step actually available in this jurisdiction, in this court, on these facts? Is the draft merely fluent, or is it right?
That last question is the one that should preoccupy us, because AI is often most dangerous when it sounds most convincing. A clean sentence, a confident tone, and a plausible-looking citation can create a false sense of security. In litigation, that is not a minor concern. It can affect pleadings, correspondence, advice, disclosure strategy, witness evidence, and submissions. An unverified error moves quickly from draft to decision-making. And once it does, the cost is no longer technological. It is professional.
Where AI is genuinely useful
Used properly, AI can be very helpful for first-stage tasks. It can generate an initial structure for a letter before action or suggest lines of inquiry from a factual chronology. It can summarise a long document set so that a lawyer can orient themselves more quickly. It can compare draft versions, identify inconsistencies, extract issues from pleadings, or turn notes into a cleaner first draft.
It can also serve as a useful challenge tool. Asking a model to identify weaknesses in your argument, to anticipate the other side’s position, or to test whether a witness statement is internally coherent can surface problems that might otherwise be missed until a later stage. Those are genuine efficiencies. But they only become professional advantages when paired with disciplined verification. Without that, they are liabilities dressed as productivity.
The evolving role
I increasingly think the lawyer’s role is not simply “lawyer plus AI.” It is something more exacting. The role is evolving from being only a producer of legal text to being an evaluator, verifier, and strategic controller of machine-assisted work. In some respects, that demands more skill than the traditional model, not less.
The basic technical barrier to entry is falling. Prompting is becoming easier; tools are becoming more intuitive; more firms are experimenting. Over time, a willingness to use AI will not distinguish anyone. It will be assumed.
What will distinguish lawyers is the quality of their scrutiny. The lawyer who spots a mischaracterised case, who recognises that a model has collapsed two different legal tests into one, who sees that output is legally plausible but procedurally useless, who identifies the missing authority or the overstated conclusion - that is the lawyer whose judgment actually adds something. And that kind of scrutiny is not a skill AI can perform on its own behalf. It requires a lawyer who understands the substance well enough to catch what the model gets wrong, including the errors that look right at first glance.
What this means for junior lawyers
For those early in their careers, there is a temptation to think that AI simply threatens junior work because it can perform some first-draft tasks more quickly. There is some truth in that. But the better view is that it changes what excellence looks like.
The most valuable lawyer will not be the one who turns documents around fastest. It will be the one who uses these tools to reach a better result while maintaining accuracy, evidential discipline, and legal credibility. The difference matters. A lawyer who can draft quickly with AI but who lets an unfounded proposition through to a filed document has not saved anyone time. They have created a problem.
Some practical observations
First, treat AI output as a draft, never as an authority. However polished it reads, it is not the endpoint.
Second, verify every legal proposition against a primary source. If the model provides a case, check the case. If it provides a rule, check the rule. If it provides a quotation, check the wording and context. This is tedious. It is also non-negotiable.
Third, be particularly careful with citations. A fabricated citation is the obvious risk, but a real citation attached to the wrong proposition is often more dangerous, precisely because it is harder to detect.
Fourth, calibrate confidence to consequence. Brainstorming is different from advice; an internal note is different from a filed document; an exploratory outline is different from a witness statement. AI is most safely employed where the cost of error is lowest, and most cautiously where precision is essential.
Fifth, keep the lawyer’s task in view. The aim is not to produce text quickly. The aim is to produce work that is accurate, strategically sound, and capable of withstanding challenge.
Where the conversation ought to go
We have spent quite a lot of time asking whether lawyers should use AI. The more interesting question is what good use looks like in a profession built on accuracy, accountability, and judgment. The answer is not complicated, even if it is demanding.
The lawyers who will stand out are not those who adopt AI most enthusiastically. They are the ones who use it most responsibly; who understand that a fast answer is only valuable if it is also a reliable one; who recognise that in litigation, accuracy is not an optional extra bolted on at the end. It is the work itself.
The real competitive advantage is not access to AI. It is the ability to verify what AI produces. That is a human skill, and it is not going anywhere.