How to Identify AI Use Cases in Your Business

Define the area of the business you are examining

Choose a customer journey, operating process, management decision or strategic objective. A workshop covering the whole organisation often produces vague ideas because participants are describing different work. A clear boundary allows the team to observe how value is created and where it is lost.

Name the result and the present constraint

Ask what outcome should improve and what currently prevents it. The constraint may be missing evidence, slow interpretation, poor prediction, repeated coordination, inconsistent decisions, avoidable rework or capacity consumed by routine cases.

Describe the observable problem before describing an AI solution. ‘Use a chatbot’ is an answer without a question. ‘Reduce repeat contacts caused by customers receiving inconsistent policy explanations’ identifies work that can be investigated.

Map the decisions and tasks

Follow the work from trigger to completed outcome. Mark where people interpret information, predict, classify, recommend, generate, search or choose an action. Record rules, systems, handoffs and exception routes. These points reveal tasks that may suit AI as well as problems that need process repair rather than a model.

Process Mapping and Analysis makes the observed route visible.

Examine the evidence available at the time

For each decision, list what the person or system can know before acting and what outcome becomes known later. AI needs inputs and a way to judge results. If later outcomes are not recorded, the business may be able to retrieve or assist but not yet learn or evaluate reliably.

Also note information that should not be used because of privacy, consent, fairness, contractual or regulatory limits.

Match the task with an AI capability

Variable language may suit retrieval or generative AI. Images may suit computer vision. Repeated outcomes may support prediction or anomaly detection. Constrained choices may require optimisation. A stable sequence with one variable task may suit an AI workflow. Work requiring contextual choice across tools may justify a bounded agent.

Keep conventional rules, reporting and automation in the comparison. The objective is a better business result, not the highest possible amount of AI.

Write a one-page use-case hypothesis

Record the user, problem, present baseline, proposed capability, input evidence, output, action, human authority, expected value, important risks and first test. State why AI may be better than the current approach and a simpler alternative.

Use conditional language. The use case is a proposition to test, not a promise that a model will produce the intended outcome.

Remove weak candidates before scoring

Remove ideas with no owner, no action connected to the output, no way to observe value or a consequence of error that cannot be controlled. Combine ideas that address the same workflow. Separate broad concepts into a first bounded use case that can be evaluated.

A shorter set of well-framed opportunities makes AI use-case prioritisation more credible.

Run discovery with the people who perform and receive the work

Leaders can identify strategic outcomes, but employees, customers and operating partners reveal exceptions and tacit work. Include process owners, frontline users, data and technology staff, risk or legal specialists and people affected by the result. This improves the use-case definition and surfaces constraints before selection.

How Marketways supports use-case discovery

Opportunity Discovery combines market, customer, technology and business evidence to form explicit hypotheses. AI Strategy and Advisory connects those opportunities with feasibility, workflow, capability and evaluation questions.