Early Case Assessment with AI: Know Your Case Before You Commit

What early case assessment actually requires

Strip away the consulting language and ECA answers four questions: What happened, in what order? Who is involved, on which side? Where does the evidence contradict itself or the client's account? And what should exist in the record that doesn't? Answer those honestly in week one and almost every downstream decision - take the case, settle it, price it, plead it - gets easier.

The reason most small practices skip it isn't ignorance, it's arithmetic. A four-hundred-page intake pile takes days to read properly, and unbillable days at that. So assessment happens implicitly, over months, as surprises surface - which is the most expensive possible way to learn your own case.

Why summaries are not assessment

The obvious shortcut - paste documents into a general-purpose AI and ask for a summary - fails at exactly the points ECA exists for. A summary compresses; assessment cross-examines. The date discrepancy between the contract and the email thread disappears in a summary, because each document was summarized faithfully on its own. The gap - the notice letter everyone assumes exists but nobody has produced - can't appear in a summary at all, because you cannot summarize a document you don't have.

Fact-level analysis works differently: every event, party, and assertion is extracted with its source, then compared across the whole set. Same event, different dates? That surfaces as a conflict with both citations. A fact asserted once, corroborated never? It's marked as standing on one document. A fact your practice area expects that no document contains? Listed as a gap. That is assessment - and it's checkable, because every line points back to a page.

A one-hour ECA workflow

• Minutes 0-10: drop everything. The whole intake pile - correspondence, agreements, filings, the client's own timeline if they wrote one. Don't curate; the point is to let the record speak, including the parts the client didn't emphasize.
• Minutes 10-40: let it read, then read the ledger. While files process, do something else. Come back to the factual record: the chronology in order, the parties, and - first priority - anything marked conflicting. Open each conflict's citations and decide which account holds.
• Minutes 40-50: interrogate the gaps. The facts your discipline expects but the record doesn't contain are your discovery list and your client-questions list, pre-written. A gap at intake is a task; a gap at trial is a problem.
• Minutes 50-60: confirm or correct. Walk the unverified queue. Confirm what checks out against its source, correct what doesn't. Your confirmations upgrade the record's confidence - and what you're left with is an assessment you can defend, not a vibe.

Judging the output like a lawyer

Whatever tool you use, hold it to three standards. First, provenance: every asserted fact should cite a document and a page you can open - a fact that can't show its source should say so plainly. Second, honesty about conflict: when documents disagree, you should see both sides with citations, never a silently chosen winner. Third, honesty about absence: the tool should tell you what it couldn't read and what the record doesn't contain, because an assessment that hides its own blind spots is worse than none.

Treat confidence scores with the same skepticism. A useful confidence number is derived from things you can check - is there a verbatim quote, does a second document corroborate it, did a human confirm it - not from the model grading its own work.

Is AI early case assessment reliable enough to act on?

Reliable enough to direct your attention, not to replace it. The right posture: the AI builds the record and shows its sources; you verify the facts that matter before acting on them. A tool that cites every fact to a page makes that verification take minutes. One that doesn't is asking for trust it hasn't earned.

How is this different from eDiscovery software?

eDiscovery platforms are built to process and produce large document populations defensibly - holds, review workflows, productions. ECA is a different job: understanding what a case-sized record establishes. Fact-first tools do the second job natively; eDiscovery tools do the first and treat assessment as something human reviewers assemble afterward.

What does ECA change for a contingency or flat-fee practice?

Case selection and pricing. On contingency, an hour of honest assessment before signing is the difference between a portfolio and a lottery. On flat fees, the gaps-and-conflicts picture is your scope: you can price the known work and carve out the surprises you can already name.

Do I need the client's permission to run their documents through AI?

Follow your jurisdiction's guidance on technology-assisted practice - the common thread is competence and confidentiality, not prohibition. Use a platform that contractually excludes training on your data, disclose the category of use in your engagement letter, and supervise the output as you would a junior's memo.