Guide · AI employees
How to Choose Your First AI Workflow
Pick a recurring task with clear inputs, a useful output, and someone who can judge the result before you automate it.
The first AI workflow in a business tends to attract every idea at once. Someone wants lead research. Someone else wants social posts. Before long, the plan includes customer support, a dashboard, and a sales assistant. Start with a task you can watch from beginning to end. You'll learn more from one working routine than from six unfinished demos.
Look at last week's work
Open the actual work queue. Look for something that happened several times and followed roughly the same path each time. Preparing a call summary, sorting incoming inquiries, or drafting a response from approved product information can be useful candidates. A task doesn't have to consume an entire job to be worth improving.
Pick three examples and lay out what happened. What arrived? Who handled it? Where did they look for information? What did they produce? What caused a delay? If nobody can reconstruct those examples, spend some time making the existing process visible before asking software to run it.
Choose work with an answer you can check
A good first task has a recognizable finish. For an inquiry summary, that might mean the customer's request, location, deadline, missing information, and suggested next action. A reviewer can compare the summary with the original message and spot omissions.
"Improve our marketing" doesn't offer the same test. A plausible paragraph could pass without helping anyone. Narrow it to something like preparing a first draft of a product email from an approved offer sheet. The copywriter can then judge accuracy, tone, and usefulness against a specific brief.
Keep the first boundary small
For a hypothetical service company, start with summarizing an inquiry for the office coordinator. Let the coordinator decide whether to call, request more information, or decline the job. Sending the reply, changing the CRM, and booking an appointment are separate steps that can be added after the summary is dependable.
This boundary makes failures easier to diagnose. If the output misses the service address, you can inspect the extraction step. If the same workflow also changed five records and sent a message, the review becomes a much larger job.
Estimate the review work too
Run the task manually with AI on a small batch before building an integration. Record how long preparation, generation, checking, and corrections take. Include the awkward examples, especially incomplete inputs. A workflow that produces a draft quickly but takes longer to repair may be the wrong first choice.
Also ask who will maintain the instructions. Product details change. Someone leaves the team. A form gets a new field. Put a name beside that responsibility rather than assuming the workflow will stay useful on its own.
Set a modest first finish line
Write a short pilot agreement before you build. It should tell the reviewer exactly what is being tried and what would justify continuing.
Keep the successful examples and the failures. Those records will be more useful when you add the next step than a vague memory that the demo looked good.
- One recurring task and one person responsible for the result.
- A small set of representative inputs, including an incomplete one.
- A definition of an acceptable output and a place to record corrections.
- A limit on what the workflow may change or send.
- A review date to decide whether to improve, expand, or stop it.