Legal AI has matured from simple automation to deeper workflow integration. These systems can now process large document sets in minutes, identify key facts and entities, flag inconsistencies, and produce preliminary outlines for questioning or drafting. The model is explicitly hybrid—attorneys still verify the record, tailor strategy, and make risk calls. The specific capabilities and pricing structures of individual platforms remain differentiated.
The shift matters because AI adoption in litigation has accelerated past the experimental phase into practical default territory. Firms are using these tools to cut time on labor-intensive work, which raises a live question for practitioners: where should the line fall between machine efficiency and lawyer oversight? Attorneys should expect pressure to adopt these workflows and should evaluate them against their own quality controls and liability exposure.