A library of AI use cases by business function, each with the workflow, the inputs, the verification step and the value to expect. It is the practical companion to Where AI Actually Pays Off, and it exists so that a business can choose a first use case from something concrete rather than from a list of capabilities.

Every entry in the library passes the same four tests: it is frequent, it consumes meaningful time, it has a cheap check, and it is contained to one team.

The best first use case is usually the least interesting one in the room.

How to use the library

  • Scan the function you are starting with, not the whole list.
  • Check the verification column first. Where the check is expensive, the use case is not ready.
  • Pick one, and use it as the basis for the readiness assessment and the ninety-day plan.
  • Ignore the score. A use case that scores highly but has no willing owner will not be delivered.

Documents and reporting

Use case The workflow The check Value
Draft report narrative Figures frozen, then narrative drafted to structure Every figure against source; claims against evidence High — senior time recovered
Draft the executive summary Key points supplied, summary drafted Confirm every conclusion is supported Moderate
Variance commentary Frozen figures and prior period supplied Every figure traced; causes confirmed by the owner High in finance
Client update drafting Prior update and current status supplied Figures and delivery claims checked High in services
Proposal sections Approved content library supplied Terms, capability claims, references High in B2B sales

Sales

Use case The workflow The check Value
Account research brief Named sources supplied; structured brief produced Open every source; confirm claims used in outreach High and immediate
Follow-up drafting Meeting record supplied Dates, price and commitments confirmed Moderate
CRM data entry Notes and threads structured into fields Seller confirms stage and forecast Moderate, improves data quality
Proposal production Standard sections from the approved library Second-person check on terms and claims High

Finance

Use case The workflow The check Value
Management report narrative Frozen figures supplied Figures to extract; consistency with prior cycle High
Policy and procedure drafting Template and brief supplied Review and ownership by the finance lead Moderate
Document summarization Long documents supplied Spot-check against the source Moderate
Analysis framing Data structure supplied The analysis itself remains human Moderate

Operations and administration

Use case The workflow The check Value
Document extraction Fields extracted to a structured form Reconcile against the source where a field drives an action High at volume
Correspondence drafting Template and case record supplied Content, dates and commitments confirmed Moderate
Meeting notes into actions Transcript summarized to actions Confirm actions, owners and dates High and low-risk
Knowledge-base maintenance Resolved cases converted to entries Confirm against current practice Compounding

Marketing and content

Use case The workflow The check Value
Adapting approved assets Approved source adapted to other formats Content matches the approved source High and lowest risk
First-draft copy Brief and brand guide supplied Factual claims, brand rules, claims register Moderate
Campaign variants Approved asset supplied Claims and brand constraints Moderate
Audience and competitor research Named source set supplied Open every citation Moderate

Support

Use case The workflow The check Value
Response drafting Knowledge base retrieved; reply drafted Check against the source; no commitments High at volume
Thread summarization Long thread summarized to structure Confirm issue and next step Moderate
Knowledge-base creation Resolved tickets turned into entries Confirm against practice Compounding
QA sampling Sample reviewed against a checklist Reviewer confirms findings Moderate

HR and people

Use case The workflow The check Value
Policy and handbook drafting Template and intent supplied HR lead reviews every clause; advisor where needed High
Job description drafting Role details supplied Confirm against the actual requirements Moderate
Internal communications Template and context supplied Tone, accuracy, sensitivity Moderate
Policy retrieval Internal documents indexed Confirm against the policy Moderate

Boundary: nothing in HR that assesses, ranks or decides about an individual belongs in a first wave, or in a drafting workflow at all. See AI for HR.

What the library deliberately excludes

The omission is as useful as the list. Four categories are absent, and each is absent for a reason.

  • Decisions about people. Screening, ranking and evaluation carry obligations that a drafting workflow cannot discharge.
  • Calculations that will be relied on. Numbers come from the system of record, however good the model becomes.
  • Anything with no cheap check. If verification takes as long as the work, the use case cannot pay back.
  • Open-ended research. “Find out about the market” cannot be verified; a bounded source set can.

Where a candidate use case falls into one of these, the answer is usually to narrow it rather than abandon the area. Research becomes bounded research; a decision becomes a summary that informs a human decision.

Choosing between them

Three rules make the choice easier.

  • Start where the check is cheapest. Reporting and documents usually beat marketing, because correctness is easier to establish.
  • Start where the owner is willing. Voluntary adoption is faster and produces the internal reference case.
  • Start narrow. One output type, one team, one measurement. The second use case is easier because the first one produced the playbook.

Frequently asked questions

What is the best first AI use case?

One that is frequent, expensive, verifiable and contained — typically drafting a recurring document or summarizing long inputs, because both have a cheap check.

Which function should adopt AI first?

Usually reporting or document production, because the output is verifiable against a source and the burden is measurable. Finance and operations also start well; marketing is often the most willing but hardest to verify.

How many use cases should we run at once?

One in pilot, one being planned. Three in parallel produces three half-adopted workflows and no reliable evidence.

Do we need different tools for each use case?

No. A general assistant covers most of the library; the differences are in the workflow, the data rule and the check.

What if none of these fit our business?

Then the library has served its purpose by narrowing the question. Look for the same shape — frequent, expensive, checkable, contained — in whatever work consumes the most recurring hours.

Should we start with the use case that saves the most money?

Only if it also has a cheap check. Where it does not, start with a checkable use case and build the capability to attempt the larger one later.

How do we know a use case is contained?

It touches one team, one data set and one output format. Where a candidate spans two teams or three systems, it belongs in a later wave regardless of the size of the prize.

Next step

Pick one use case, score it against the four tests, and run the readiness assessment on it. See Choosing Your First AI Use Case and The AI Use-Case Prioritization Matrix, or book an AI adoption call and we will select and design it with you.

Sources

  • Library entries and their checks reflect the workflows documented across this program; where figures appear in the linked guides, they are cited there with their source and date.

No statistic in this asset is invented.