AI Agents for Business: How to Choose Your First Workflow

Someone on your team spends part of every morning opening the same systems, finding the same information and preparing the same kind of update. The work needs judgement, but much of the effort goes into getting everything ready for that judgement.

That is a useful place to start looking at AI agents for business.

The first decision is choosing a piece of work worth improving. You need a clear view of what happens today, where the time goes and what would count as a better result. Choosing the technology comes after that.

This guide will help you compare possible workflows, decide whether an existing tool could do the job and write a brief for a useful first pilot.

What does an AI agent do in a business?

An AI agent uses a language model to interpret a request and choose actions through connected tools. Depending on its permissions, it might search approved documents, retrieve an account record, ask for missing information or prepare a change for someone to approve.

The term also appears on products built around fairly fixed workflows. It helps to ask what the system can actually decide. Does it follow a sequence set by a developer, or can it choose which step to take next?

Anthropic's explanation of agents and workflows makes this distinction and recommends beginning with the simplest approach that can solve the problem. An agent adds value when the work needs flexibility. Predictable steps may be better served by conventional automation.

For a buyer, the practical questions are straightforward: what information can it access, what can it change and when does a person take over?

Start with work your team can explain

Ask the person who does the work to walk you through a recent example. Have them show you the emails, documents, screens and decisions involved.

You might discover that preparing an account update takes a few minutes of writing and much longer finding the right facts. Or that a request waits in a queue because nobody knows which team should handle it. Those are different problems and need different solutions.

Write down the trigger, the information needed and the finished result. Include the awkward cases. A process that looks simple on a diagram may depend on knowledge that only one employee has.

Start with a narrow task that someone already owns. “Prepare an account briefing before a client meeting” gives a team something concrete to investigate. “Improve sales with AI” leaves too much undecided.

Four workflows to consider

These are illustrative starting points, not client case studies. Some may need an agent, while others could be handled by an existing product or a simpler automation.

Account briefing

Before a client meeting, an account manager may need to read notes, check open requests and find recent changes. A useful first version could prepare a short briefing with links back to the original records.

Keep it focused on preparation. Updating a sales forecast, making a commitment to a client or sending an email introduces a different level of responsibility. Those actions do not need to be part of the first pilot.

Internal knowledge requests

An employee needs to find an approved procedure or understand how to handle an unusual request. A system that retrieves the relevant material and explains where its answer came from could reduce searching.

Before building it, check whether the documents agree. If two departments use different versions of the same procedure, someone needs to resolve that conflict. The system also needs a way to say that the available information is insufficient.

Incoming request triage

A shared inbox receives requests written in different ways. The useful work may be recognising the type of request, finding an existing account and suggesting who should handle it.

Keep this separate from automatically resolving every request. During a pilot, staff can review the suggested routing while you learn which cases are clear and which need more context.

Document intake

A team receives documents and copies selected details into an internal system. AI could help interpret varied layouts, identify missing information and prepare a draft record.

Test ordinary document processing tools as well. If every document follows the same format, a fixed extraction process may be sufficient. An agent becomes a candidate when the next step depends on what the document contains or which information is missing.

How to choose between the candidates

A workflow deserves a closer look when it happens often enough to matter, has accessible source information and produces a result someone can check.

For each candidate, answer these six questions with the person responsible for the process:

1. How often does the work happen, and how much effort does it take today?
2. Which part needs interpretation rather than a fixed rule?
3. Can we access the necessary information through approved systems?
4. Can someone recognise a correct result without redoing all the work?
5. What happens if the output is wrong, incomplete or late?
6. Who will review the pilot and own the process afterwards?

A frequent task with a modest scope can make a better first project than an ambitious process involving several departments. The smaller task lets you learn about real inputs and review effort without changing everything at once.

Do not force a numerical score when you are missing the basics. If nobody can explain how correctness will be checked, that candidate needs more investigation before development starts.

Use an existing tool or commission a custom build?

Check the software your team already uses. It may have a feature that covers the task, or a product in that category may solve it with limited configuration.

An existing tool is worth testing when the workflow is common and its permissions, integrations and review controls fit your needs. Ask to see it working with representative examples. A polished demonstration using perfect inputs will tell you less than a test involving the awkward cases your team sees every week.

Custom development becomes worth considering when the workflow crosses systems, depends on unusual rules or needs controls that the available tools cannot provide. That still needs a business case. Maintaining another piece of software is an ongoing commitment.

Compare the complete cost: configuration or development, integration, review time, usage charges and support. Our AI agent development cost guide explains the factors to include when planning a budget.

Write a pilot brief before asking for a proposal

A useful brief describes the work closely enough that a supplier can discuss the difficult parts. It should also give your own team a shared definition of success.

Here is an illustrative brief for account preparation:

When an account manager requests a meeting briefing, retrieve the approved account record and recent activity. Prepare a summary with source links and a list of missing information. The account manager reviews the briefing before using it. The system must not contact the client or change account records.

That brief identifies a trigger, a result and limits on what the system may do. The next conversation can focus on access, source quality and how the team will assess the summaries.

Add these details before implementation:

1. The process owner and the people who will use the result.
2. The systems and information the pilot may access.
3. The actions it may take and those that require approval.
4. Examples of ordinary, difficult and incomplete requests.
5. What should happen when information is missing or a system is unavailable.
6. The measures and acceptance criteria you will use to decide whether to continue.

If the task involves sensitive information or consequential decisions, involve the people who already own those responsibilities while setting the scope. Do not leave access decisions until the software is ready to connect.

Measure the work that remains

An output produced quickly can still take too long to check. Measure the whole task, including reviewing, correcting and dealing with exceptions.

For example, suppose a briefing currently takes eight minutes to prepare. During a pilot, reviewing and correcting the generated briefing takes five minutes. At 100 briefings, that would release five hours of staff time before accounting for support and operating effort. These are illustrative numbers, not a forecast of what a particular agent will deliver.

Time released is not automatically a cash saving. It may mean the team can respond sooner or handle more work within existing capacity. Decide which outcome matters to your business before presenting the pilot as a success.

Alongside time, record factual corrections, missed information, cases sent back to a person and useful tasks completed. Compare similar work. Do not put the easiest requests into the pilot and compare them with the full range handled by the team.

Agree what would make you stop or narrow the project. Repeatedly exposing information to the wrong user, inventing important facts or requiring complete manual rework would each need attention before broader use.

Plan who looks after it

Someone needs to own the workflow after the pilot. Source documents change, integrations fail and users find cases that were not in the original test set.

Agree who reviews problems, approves changes and decides when the system should pause. Include that responsibility when comparing a packaged tool with a custom build.

Our guide to AI agents in production covers the engineering work behind permissions, evaluation, monitoring and ongoing operation. Those details become easier to plan once you have chosen a specific workflow.

Questions to settle before you start

Do we need an AI agent or ordinary automation?

If the inputs are predictable and the next step follows a clear rule, begin by evaluating ordinary automation. Consider AI when interpreting language or choosing between possible steps is a meaningful part of the work. A pilot should establish whether that added flexibility is useful enough to justify its cost and review effort.

Does an agent need permission to change our systems?

No. A first version can retrieve information and prepare a draft for a person to review. If you later allow changes, define the permitted actions, approval points and recovery process before enabling them.

Can we start if our data is untidy?

You may be able to start with one limited set of reliable information. Identify which sources are current, who owns them and who may access them. If the task depends on missing or contradictory records, resolving those issues belongs in the project scope.

What should we ask a development supplier?

Ask how they will test the difficult cases, control access, handle incomplete information and measure review effort. Request a clear explanation of what the pilot will prove, what it will leave unresolved and who supports it afterwards.

Bring one workflow to the conversation

Choose a task your team can show someone. Bring a recent example, the systems involved and a description of what a useful result would look like.

Redevon IT's AI agent development service covers custom agents and integrations for existing business workflows, with human approvals, evaluation and ongoing support considered as part of the scope.

If you have a task in mind, discuss your AI workflow with us.