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P E E R T O P E E R M A G A Z I N E · S P R I N G 2 0 2 6 55 THEMES, IMPEACHMENT, AND STRATEGY As depositions accumulate, themes emerge across witnesses. Some align tightly. Others carry tension that needs attention. AI compares testimony across ses- sions and organizes statements by topic so that agreements and contradictions are clear. This cross-witness view helps the team understand how the narrative is developing, where the record is strong, and where careful explana- tion will matter. Judges and juries trust a record where testimony fits together and differences are handled openly. Surfacing themes early gives the team time to address weaknesses before they solidify. Impeachment depends on preci- sion. Small shifts in wording can make a big difference in how a fact finder views credibility. AI ex- cels at finding these shifts across transcripts and presenting them with context. Reviewing those lines with the witness lets the lawyer explain how impeachment works and practice clear answers that acknowledge differences without confusion. When a differ- ence has a sound explanation, the witness can give it. When a prior answer was mistaken, the witness can say so with clarity. Avoiding evasion and focusing on accuracy reduces the impact of A GLIMPSE INSIDE AI'S IMPACT ON TRIAL WEEK The following hypothetical, drawn from common litigation workflows, illustrates how these methods come together under time constraints. A trial team entered the first week of a products case with more than 50 prior transcripts for expert witnesses. The team needed to prepare two key witnesses while also planning cross-examinations of three opposing experts. Time was tight, and the record spanned thousands of pages. The team used an AI platform to ingest the full set of transcripts and the core exhibits tied to them. In record time, the system produced a topic map for each witness, a set of language-shift flags with page and line refer- ences, and a cross-witness view of where accounts aligned or conflicted. For the opposing ex- perts, the team requested a list of statements that differed from the experts' prior testimony in other matters. The output linked each current statement to earlier lines, with page and line references and short notes on the nature of the difference. Armed with this material, the team updated cross-examination outlines. For one expert, the tool surfaced a definition of a key term that had narrowed over time. The team built a short series of questions that walked through the older definition, the current ver- sion, and the implications of the change. During cross, the lawyer used the page and line citations to read the prior line accurately and to give the expert a fair chance to explain. The exchange was clear and concise, and it anchored a theme the team developed in closing. During the trial week, the team updated these materials daily as new testimony came in. The AI platform slotted fresh transcripts into the topic map and adjusted the cross-witness comparisons. This rhythm kept preparation focused and reduced surprises. This example illustrates two practical points. First, the speed and depth of large-scale compari- son change what is feasible inside trial timelines. Second, the value depends entirely on the lawyer's judgment about what to empha- size, what to set aside, and how to present the material fairly.

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