Strategy in litigation has historically been a function of experience. The lawyer who has tried fifty cases in front of a particular judge knows things the lawyer trying their first one doesn't. AI partly democratizes that experience.
The first strategic decision in litigation is whether to litigate at all. AI-assisted analysis can sharpen that decision by surfacing the closest comparable cases, the success rates on similar theories, and the typical resolution paths.
Case Selection
We use this analysis to set realistic expectations with clients before a case is filed. A clear-eyed view of likely outcomes is more valuable than confident-sounding advice that turns out to be wrong.
Argument Selection
Once a case is underway, the question becomes which arguments to lead with. AI can surface the patterns in a particular judge's rulings, the language that has historically resonated, and the procedural moves that have shifted comparable cases.
None of this replaces the litigator's judgment. It informs it. The best litigators we know read the AI-generated brief carefully and then disagree with parts of it. That's the right relationship.
Settlement Timing
Settlement timing is one of the most consequential decisions in any case, and one of the hardest to get right. AI tools that estimate settlement value at different procedural stages give lawyers and clients a clearer view of when to move.
These estimates aren't predictions — they're priors, calibrated against history. Combined with the specifics of the case, they help structure the conversation between attorney and client about when to take a deal.
Where AI Falls Short
AI is useful in the parts of litigation that look like other litigation. It's less useful in the parts that look like nothing else. Genuinely novel cases — new claims, new defendants, new fact patterns — require strategy that the historical record can't fully inform.
Recognizing which case is in front of you is itself a judgment call, and one of the most important a litigator makes.
