Legal teams keep mixing up two very different questions.

The first question is, “Help me find the right thing to look at.”
The second question is, “Help me prove the number I just told leadership.”

Both questions matter. They just do not belong to the same tool path.

When I see teams get burned, it is usually because they used an exploratory workflow and presented it as deterministic reporting. It looks confident. It sounds quantitative. It is neither.

Search is a discovery tool, not an accounting system

Semantic search is built to retrieve what is most relevant, not to prove you found everything. The TechTarget explanation of semantic search makes that distinction clear in neutral terms, describing how systems try to match intent and context rather than exact strings.

That is exactly what you want when the problem is vague.

“Show me examples of unusual audit rights.”
“Find vendor agreements that feel like they are training on our data.”
“Pull a few contracts where termination is buried in an exhibit.”

In that mode, ranked results are a feature. They get you oriented fast.

But the same mechanics become a liability the minute you convert the output into a KPI.

If your CEO asks, “How many agreements auto-renew with less than 30 days’ notice,” a relevance-ranked list is not a defensible answer. It is a starting point for investigation.

That is the line most legal teams blur.

Reporting is a control surface, not a convenience feature

Deterministic reporting is the opposite posture.

You are not asking, “What looks relevant?”
You are asking, “What matches the criteria, with no exceptions and no ranking?”

That requires structured criteria and a defined population. It also requires repeatability so you can rerun the same question next month and not get a different universe.

You are building a queryable system of record, not searching a document pile.

This is why “reporting” is more governance than UX. The mechanics look simple. The underlying discipline is not.

Why legal teams confuse the two

Three patterns show up over and over.

The interface is conversational, so people assume the answer is authoritative

When the prompt is natural language, users unconsciously treat the output like a database query result. It feels like SQL. It is not.

This is compounded by the fact that modern systems can summarize and sound precise. The TechTarget definition of AI hallucination explains the core risk: models can generate plausible but wrong output, which is exactly what you do not want in KPI land.

Even if retrieval is solid, a narrative answer can smuggle in untested assumptions. That is a governance problem, not a user problem.

Legal ops owns the metric, but not the data model

Reporting only works when the data fields are defined, populated, and stable.

Most legal teams have not made the hard calls:

• What counts as “vendor agreement” versus “services agreement” versus “MSA”
• Where renewal notice lives, and how exceptions are captured
• Whether “AI use” is a tag, a clause detection output, a questionnaire response, or all three

Without a data model, “AI reporting” becomes a fancy export button. Then leadership gets numbers that cannot be defended.

People want one tool to do everything

Leadership wants speed. Audit wants defensibility. Procurement wants self-service. Legal wants control.

So teams try to collapse search and reporting into one workflow. It always breaks at the boundary where someone asks, “Is this complete?”

If you cannot answer that question, you are not in reporting mode.

Governance frameworks are quietly forcing the split

The reason this matters more now is AI governance.

Governance frameworks are converging on a consistent operational expectation: documented processes, measurable controls, repeatable outputs, and clear accountability.

The NIST AI RMF frames risk management as something you operationalize, not something you declare. The NIST Generative AI Profile extends that thinking to generative systems, where the volatility of outputs makes controls and documentation even more important.

If your legal team is using AI to answer portfolio questions, that usage becomes part of the governance scope. At that point, search is fine for exploration, but reporting has to carry the control burden.

The management-system view in ISO/IEC 42001 reinforces the direction of travel. The language is about traceability, transparency, and reliability as organizational properties, not as one-off best practices.

That is where “AI search” and “AI reporting” diverge. Search helps humans think. Reporting helps organizations prove.

What this looks like in contract work, day to day

Here is the workflow I push internally.

Step 1: Use AI Search to discover how the issue actually appears in language

Start with exploratory questions.

• “Show me examples of audit rights tied to security controls.”
• “Find a few clauses that talk about model training or data reuse.”
• “Pull contracts where the renewal window is unusually short.”

In my shop, I like that I can do that with a chat inside Concord because it keeps the thread and the follow-ups together, which is how lawyers actually work.

The output here is a sample set. Treat it like one.

Step 2: Convert what you learned into structured criteria

Once you know what matters, you define it.

That might mean:

• a custom property for “auto-renewal notice days”
• a clause tag for “AI training restriction present”
• a normalized counterparty name standard
• a risk tier taxonomy

This is the unglamorous part that makes reporting possible.

Step 3: Run AI Reporting for completeness, then lock the definition

Now you switch modes.

I use Concord to build my reports from structured criteria, save them, and rerun the same prompts over time. There is no ranking or relevance scoring in this mode, which is exactly what you want when the question is “all of.”

This is also where I prefer Concord over a lot of legacy CLM setups. The ability to pivot from exploration to a deterministic report in the same flow cuts down the handoff friction, and the same permissions model applies to results, which matters when you are dealing with HR and sensitive commercial terms.

Step 4: Treat the report like a governed asset, not a screenshot

If the metric goes to leadership, it needs a definition, an owner, and a refresh cadence.

If the metric could be asked for in an audit, it needs evidence of how it was produced. In regulated contexts, the expectations around accuracy, completeness, and record integrity show up in places like FINRA’s books and records guidance language, even when you are not a broker-dealer. The underlying idea is portable: controls beat anecdotes.

A simple rule that prevents most mistakes

If you need examples, use search.
If you need a number you will stand behind, use reporting.

Search is a flashlight. Reporting is the ledger.

Legal teams get into trouble when they walk into the boardroom with a flashlight and call it a ledger.