AIVAX

Practical guides and case studies

Common use cases by industry

Compare practical agent uses across eight industries and choose a first project with clear evidence, limited permissions, and manageable risk.

  • Unit 4 of 6
  • 12 min
  • Beginner

In this unit, you will learn

  • Identify bounded agent use cases in different industries.
  • Match each use case to the knowledge and tools it needs.
  • Recognise sector-specific risks and human decision boundaries.
  • Compare candidate projects using evidence rather than novelty.

An agent that helps a retailer find a parcel and an agent that helps a school explain enrolment share much of the same structure. Both need clear instructions, approved information, appropriate access, and a route to a person. Their risks are different, however. A wrong shop opening time is inconvenient; a wrong clinical instruction can cause serious harm.

Use this guide as a menu of bounded projects, not a catalogue of promised returns. A use case describes a particular person trying to achieve a particular outcome. “AI for healthcare” is an industry label. “Help an authorised receptionist find the published appointment preparation leaflet” is a use case that can be designed and tested.

Start with the work, not the industry label #

Useful first projects usually involve repeated questions, an identifiable source of truth, and outcomes that someone can verify. A source of truth is the authoritative system or document for a fact. It might be an order system for shipment status or an approved policy for reimbursement rules. The model’s general knowledge is not a substitute for either.

Find and explain

Search approved information and explain it clearly. The main work is preparing sources, respecting permissions, and showing supporting evidence.

Prepare for review

Draft a summary, form, or checklist for a person. The reviewer must have enough evidence and time to check it, rather than merely approve automatically.

Take a bounded action

Use a tool, a defined software operation, to change a record or request a service. Permissions, confirmation, duplicate prevention, and recovery become essential.

Risk combines what could go wrong with how serious the consequences would be. “Only answering questions” can still be high risk if the answer influences treatment, credit, employment, or a legal deadline. Evaluate the consequence, not just whether the agent presses a button.

Explore the industries #

Each tab gives three possible uses, their usual information and tools, and a boundary for the first version. These examples are fictional design patterns, not statements that any specific organisation has deployed them.

Use cases: explain returns policies, look up an authenticated shopper’s order, and prepare a support ticket for a damaged item. The needed knowledge includes current delivery terms, product instructions, and approved warranty rules. Typical tools read authorised orders and create confirmed tickets.

Main risk: exposing another customer’s details or inventing a refund commitment. Keep refunds and payment changes outside the first version, and require identity checks for private orders. A product description does not prove that an item is currently in stock. The live inventory system owns that fact.

Compare the boundaries before comparing benefits #

The same technical action can carry very different consequences. Creating a draft maintenance ticket is not equivalent to approving a financial transaction. A human review must occur before the consequential action, with enough context to judge it; reading a log afterwards is monitoring, not approval.

Pattern Suitable first output Boundary to test
Retail support Supported policy answer Customer-specific information stays private
Finance administration Completeness checklist No implied approval or personalised advice
Healthcare administration Published service information No diagnosis or treatment recommendation
Education support Resource explanation Student records and assessment decisions stay protected
Real estate service Confirmed viewing request No discriminatory filtering or invented listing facts
Logistics support Evidence-based status summary No guaranteed date without a valid commitment
Professional services Labelled draft No cross-client information leakage
Public service guidance Clear next-step explanation No false official determination

For the underlying design, read Adding guardrails. For potentially consequential workflows, Human in the loop explains why approval must be an enforced stage rather than a polite suggestion in the prompt.

Estimate value from local evidence #

Value might mean shorter searches, fewer repeated questions, better completed forms, or less rework. Start with a baseline: observe the current process before introducing the agent. Include the time spent preparing documents, reviewing outputs, maintaining integrations, and handling mistakes.

Illustrative weekly time recovered by use case type

Invented planning example, not measured savings or an industry comparison. Real net savings must subtract review, maintenance, and rework.

The chart is deliberately organised by work type, not by sector. A small firm with poorly maintained documents might gain less from an assistant than from repairing its knowledge base first. Conversely, a modest retrieval assistant can be useful where staff repeatedly search a clear, reliable reference library.

Questions to settle before a pilot #

Should we automate the highest-volume task first?

Volume matters, but so do consequence and recoverability. Prefer a frequent task with reliable evidence, limited permissions, and an easy route back to a person. A high-volume task that changes legal or financial outcomes may need much more preparation than a lower-risk information service.

Can we use the same agent across departments or clients?

Shared instructions may be reusable, but access rights and information must remain correctly separated. Confirm the identity and permitted scope before searching or acting. Do not rely on the model to remember which confidential passages it should hide from each user.

What if the sector is regulated?

Involve the organisation’s qualified legal, compliance, privacy, and domain specialists before launch. This guide is not a determination of applicable law. They should define permitted uses, required records, retention, disclosures, accessibility, and human oversight for the actual jurisdiction and service.

Select one use case, one accountable owner, and a small set of measurable outcomes. Use Testing and evaluating agents to turn the main risks into concrete test cases. Only expand after the first boundary works under ordinary mistakes and deliberate attempts to bypass it.

What’s next: keep the glossary and cheat sheet nearby while planning your own bounded project.

Knowledge check

Which characteristic most strongly supports choosing a first agent pilot?

Type to search the documentation.