AI Use Case Identification for UK SMEs

In short

Most SMEs do not have an AI problem. They have a systems problem. The CRM does not talk to the accounting tool, the accounting tool does not talk to the inbox, the inbox does not talk to the project management tool, and a person is re-keying the same data five times a week. Use case identification is the structured way to find which of those broken seams will pay back fastest when connected and automated, and where AI genuinely adds value on top.

Wingenious narrows your candidate list to five use cases per business, ranked by effort, impact and risk, with reasoning a board can sign off in a single readout. Five-page output forms the centrepiece of the Readiness Audit at £2,450 across five days. Standalone half-day workshop available from £1,500 if you already know your readiness.

Why this matters more than the build

The build is where most SMEs think automation fails. In 2026 that is rarely the truth: modern tools (Make.com, Claude Code) can implement workflows reliably for any well-scoped use case. The failure mode is upstream. Three patterns repeat across SMEs that have already spent on AI or automation and have nothing to show for it:

1. The vendor-pitch pick. Someone went to a conference, met a friendly product manager from a US vendor, and brought back a use case that suited the vendor more than the business. The build technically works; the ROI never materialises.
2. The brainstorm dump. A consultancy ran a half-day workshop and produced forty ideas. The team is paralysed: there is no defensible reason to pick any specific idea over the others, so nothing gets implemented.
3. The vanity build. Someone senior wanted a chatbot on the homepage because everyone else has one. It costs £20,000, generates two leads a quarter, and quietly disappears off the roadmap.

The Wingenious framework prevents all three by enforcing a written, ranked output with explicit reasoning. The board sees the trade-offs in one page; the dissent is recorded; the chosen use case has commercial logic behind it.

What we are actually looking for

The five candidate use cases will usually fall into one of three shapes. The framework does not assume AI is the right answer; sometimes the answer is simpler.

1. Integration. Two or more systems that should be talking to each other, but are not. A CRM that should hand structured leads to a sales tool. An inbox where supplier invoices should flow into accounting. A booking system where confirmations should sync with the diary. The fix is often workflow automation with light AI for data extraction or matching.
2. Routine admin automation. Repeatable tasks a human does dozens of times a week: tagging, categorising, drafting, routing, reminders, follow-ups, exports, reports. The fix is automation with AI doing the bits that require reading meaning from unstructured inputs.
3. Genuinely AI-shaped work. Tasks where a model is doing something a rules engine cannot: classifying sentiment, summarising long documents, answering customer queries from a knowledge base, drafting context-sensitive content. The fix is AI as the core engine, with workflow plumbing around it.

The ranking output tells you which shape each candidate is. That matters because it sets honest expectations on cost and time before any build starts.

How we identify use cases

The five-step process runs across days two and three of the Readiness Audit week, or as a standalone half-day workshop.

1. Workflow mapping

Two to three structured interviews with the people who actually run the business. We map what they do hour by hour for a typical week. Not what the SOPs say they do. What they actually do. The output is a workflow inventory grouped by function: sales, marketing, operations, finance, customer support, admin, compliance.

2. Pain identification

For each workflow, we capture where it hurts. Where do the seams between systems leak time, money or attention? Where do mistakes happen most often? Where does the team complain unprompted? Where is the bottleneck during a busy week? Pain is the precursor to ROI; workflows that nobody finds painful are usually not where the automation money is.

3. Shape assessment

Not every pain is automation-shaped. A bad office layout is real pain; no software fixes it. Candidate workflows qualify for the ranking if they meet four tests:

• Repeatable. Same shape, same inputs, same outputs across many instances. Bespoke judgement on every instance disqualifies.
• Reachable data. The information the workflow needs is accessible: in a database with an API, a file store, an inbox, a scanned archive, a SaaS endpoint. Genuinely trapped data (paper-only, single-vendor closed format) is a different problem first.
• Bounded judgement. The right answer is knowable from the inputs without specialist intuition or external context the build does not have.
• Real volume. The workflow runs frequently enough that automating it actually pays back. Five times a year does not earn a four-week sprint.

Workflows that pass all four tests become candidate use cases. Workflows that pass three are usually still worth a Quick Win build. Workflows that pass two need a precursor fix (data cleaning, process documentation, basic systems integration) before any deeper work.

4. Effort × Impact × Risk scoring

Each candidate gets scored on three axes, 1 to 10 each.

• Effort. Build complexity, integration count, data preparation needed, regulatory overhead. Higher is harder.
• Impact. Direct revenue, cost saved, time recovered, error rate reduction. Higher is bigger.
• Risk. What goes wrong if the workflow gets it wrong. Reputation, compliance, customer trust, financial exposure. Higher is riskier.

The scores are not point estimates. They are honest ranges (e.g. 5 to 7) so the conversation can argue with each number rather than treat the ranking as gospel.

5. Ranked recommendation

Final output: five candidate use cases, ranked by a composite score that weights impact heavier than effort, with risk as a multiplier (a 10-risk use case ranks lower even if impact is high). The page shows the reasoning, the named tools, the rough price estimate, and the recommended sequence (which to build first, which is best held back).

What lands in your hand

The use case identification deliverable is five pages inside the wider 20-page Audit report:

1. Workflow inventory with pain hotspots marked and broken-system seams highlighted.
2. Five ranked candidate use cases with reasoning.
3. Effort × impact × risk scores for each candidate, with ranges and dissent recorded.
4. Recommended sequence for the first 90 days.
5. Price and timeline range per candidate, calibrated to 2026 Wingenious offers (Quick Win £1,500 to £3,500, Sprint from £8,000, Custom Build from £9,950 or retainer).

This is read in an hour and acted on the same week.

Common shapes in UK SMEs

The same patterns recur across sectors. None of these are predictions; they are observed shapes:

• Lead-to-CRM automation. Form fills, inbox enquiries, partner referrals flowing into the CRM cleanly, with duplicates suppressed and lead source tracked.
• Quote-to-cash plumbing. Quote sent, accepted, invoiced, paid, reconciled, without re-keying between four systems.
• Document handling at the admin layer. Invoices, purchase orders, delivery notes, certificates, KYC paperwork extracted, classified and routed automatically.
• Inbox triage and drafting. Categorising incoming email, drafting replies, escalating the unusual.
• Reporting and management dashboards. Pulling data from disconnected systems into a single weekly management view.
• Customer support tier-one. Resolving 60 to 80 percent of common queries without a human. Sits on Gorgias, Zendesk, Tidio or custom builds.
• Internal Q&A on company knowledge. A trained assistant over policies, SOPs, contracts, product documentation.

Most SMEs find their top-ranked candidate falls into one of these seven shapes. The ranking work narrows down which one matters most for your specific business.

When use case identification points sideways

Three scenarios where the workshop output recommends a precursor rather than a build:

1. Your data is too scattered. The audit will recommend a data-cleaning Quick Win or sprint before any deeper build. Trying to skip ahead burns budget on a workflow that struggles with bad inputs.
2. Your processes are not documented. If the team cannot describe the workflow to a colleague, neither a Make.com scenario nor an AI agent can learn it either. The recommendation may be process documentation first.
3. Your team is not ready. Cultural readiness matters. The Readiness Audit’s People dimension captures this; sometimes the right first move is an AI Training cohort, not a build.

We say all three on the readout call when they apply. Honest sequencing matters more than selling the next product.

Engagement options

Three ways to get to a ranked shortlist:

1. Standalone workshop. Half-day, on-site or remote, up to ten attendees. From £1,500. You leave with the five ranked candidates and a one-page summary. Best when you have already done a readiness review and just need use-case clarity.
2. Readiness Audit. Five days, £2,450. Use case identification embedded inside the wider audit: readiness scoring, governance posture, funding eligibility, 20-page report, 60-minute founder readout. Recommended first engagement. 50% of the fee (£1,225) credited against any subsequent Wingenious engagement booked within 60 days.
3. Feasibility Study. Two to three weeks, £3,950. After use case identification has picked the candidate, the feasibility study models it in depth: ROI projection, built-vs-buy, vendor shortlist, risk register, board-ready business case.

Related capabilities

AI strategy development · AI readiness assessment · AI business case · AI ROI calculation · Built-vs-buy analysis

Sectors where use case identification matters most: law firms, ecommerce, construction.