AI Workflow Examples With Inputs, Checks and Results

An AI workflow connects an input to a defined task and a usable result. The examples here use a fixed sequence: supply the material, request one transformation, check the result and hand it off. You can run them manually in a chat assistant before adding integrations.

Example: turn approved meeting notes into a recap

Input: confirmed notes with decisions, owners, dates and open questions. AI action: create a recap table and quote the supporting note for each row. Check: the meeting owner compares every decision and date with the source. Result: the owner sends the approved recap; unsupported statements stay open questions.

If the draft turns “the team discussed Friday” into “the team agreed Friday,” reject it. Update the prompt to require NOT APPROVED for a discussion without a decision, then rerun and review the full table.

Use this fictional packet to try the workflow:

The team discussed launching Friday but did not choose a launch date.
Maya will send the revised landing-page copy to Lee by Wednesday.
Lee will review the copy after Maya sends it. No review deadline was set.
The team approved using the existing signup form for the launch.

Paste it into your assistant with:

Turn these notes into decisions, actions and open questions.
For each action, include owner and due date. Use "not agreed" when absent.
Quote the source sentence that supports each row.
Keep a discussed option separate from an approved decision.

The expected recap below is an answer key, not a recorded model response:

The meeting owner checks the supporting sentences, then copies the approved rows into the team’s normal notes or task system. Completion means the owners and unresolved launch date are visible to the team. It does not mean the AI has created or assigned tasks automatically.

Example: update a page from a changed source

This fictional content-refresh task changes two facts while preserving the offer. The AI’s job is to identify and rewrite affected copy, not invent a new campaign.

OLD PAGE:
Join our Thursday workshop at 5 p.m. The session takes place online.
Register through the workshop form. A recording is included.

APPROVED UPDATE:
The workshop now starts Friday at 11 a.m.
There will be no recording. It remains online and uses the same form.

Request a revised paragraph and a change log with old value, new value and supporting source. A correct draft is:

Join our online workshop Friday at 11 a.m.
Register through the workshop form. No recording will be available.

Check that both the schedule and recording statement changed. A draft that fixes the day but leaves “A recording is included” fails the task. Follow up: “Compare every factual sentence against the approved update. Replace the old recording claim as well as the schedule.”

The editor then checks the rest of the page for the same facts, including headings, captions and any event metadata. The AI only saw the supplied paragraph; it cannot establish that every instance on the website is fixed. Publish through the normal page-editing process and inspect the rendered page.

Use this workflow when you have an authoritative update. If you only suspect the old facts are wrong, verify them before asking AI to rewrite the page.

Example: draft a support reply from a policy

For this exercise, both the policy and ticket are fictional. They demonstrate matching a request to supplied rules, not advice about a real store’s obligations.

POLICY:
For damaged items reported within 14 days of delivery, ask for the order
number and a photo. A support reviewer then decides the available remedy.
Do not promise a refund or replacement before review.

TICKET:
My mug arrived yesterday with a cracked handle. What should I do?

Ask for an internal draft that applies only this policy, identifies missing information and avoids promising a remedy. An acceptable reply is:

I'm sorry the mug arrived with a cracked handle. Please send your order
number and a photo of the damage so our support team can review the case.

The support agent checks the actual policy, timing and required information before sending. If the draft says “We’ll ship a replacement today,” replace that line with the review request. If the ticket instead says the mug arrived a month ago, this packet does not establish what remedy applies; send it to the person responsible for exceptions rather than extending the 14-day rule yourself.

Completion is a reviewed reply or a clearly assigned exception. These are different outcomes, and both need somewhere to go in the support process.

Select the AI step

Choose a workflow you can finish

Start with the meeting example when the information is already in a short note. Use content refresh when a known fact has changed. Choose support drafting when the relevant policy is available and someone can handle exceptions. If the task depends on missing information, collect it before generating an answer.

OpenAI documents drafting and summarization among ChatGPT’s capabilities. These examples use those basic text tasks; they do not require tool connections, paid automation or an agent that chooses its own actions.

Make the handoff repeatable

For a second run, keep the same output fields and change the input. Check a difficult case as well as a clean one: an undecided deadline, a contradictory update or a ticket outside the stated policy. Record what the reviewer changed and why.

Automate only after you know where the accepted result and exceptions go. If reviewers rewrite nearly every output, revise the task or source packet first. Moving a weak draft through more systems will not fix it.

Questions about AI workflows

Build the integration only after the process is stable: How to Automate Tasks With AI.