Make and ChatGPT: simple automation examples
Concrete scenarios to connect ChatGPT to emails, spreadsheets and internal tools with Make.
Quick view
Concrete scenarios to connect ChatGPT to emails, spreadsheets and internal tools with Make.
This content helps you
- what can be automated
- which tools can be used
- how to structure the workflow
- where human validation should stay
What is covered
- 1What can be automated
- 2A simple workflow
- 3Tools you can use
- 4Limits and precautions
- 5When to request a diagnostic
Section 01 · guide
What can be automated
Make and ChatGPT: simple automation examples usually starts with a repetitive task: information arrives, someone reads it, decides what it means and performs the next action. AI can help classify, summarize, draft or route that information.
The safest first version does not remove human control. It prepares the work, highlights exceptions and lets a person validate important outputs.
Section 02 · method
A simple workflow
- 1Identify the source: email, form, spreadsheet, CRM, document or ticket.
- 2Define what the AI should read, classify or summarize.
- 3Create a draft, alert, task, row or internal note.
- 4Keep sensitive or unusual cases for human review.
- 5Measure the time saved before adding more complexity.
Section 03 · guide
Tools you can use
Many first automations can be built with Make, Zapier, Google Sheets, Notion, Airtable, a CRM and an AI assistant or API. The right stack depends on the tools already used by the team.
A small business does not always need a heavy system. A clear workflow, a reliable prompt and a simple validation step can already create a strong return.
Section 04 · method
Limits and precautions
- 1Do not send sensitive data to a tool without checking privacy rules.
- 2Do not let AI make commercial, legal or financial decisions alone.
- 3Test the workflow on real examples before using it every day.
- 4Document the exceptions that should stop the automation.
Section 05 · guide
When to request a diagnostic
A diagnostic is useful when the task involves several tools, several people, confidential data or recurring business impact. It helps define the process before choosing the technical setup.
The goal is not to sell a generic tool. It is to recover time, reduce friction and give the team more peace of mind.
Frequently asked questions
Can this be done without coding?
Often yes. Many first versions can be built with tools like Make, Zapier, spreadsheets and a well-framed AI prompt.
Should everything be fully automatic?
No. For a first version, it is safer to automate preparation and keep human validation for sensitive cases.
How do I know if this automation is worth it?
Look at frequency, time lost, number of people involved and risk of mistakes. If the task repeats often and follows stable rules, it is a good candidate.
What data should I prepare first?
List the source, the fields needed, the expected output, the simple cases and the exceptions that should stay human.
What are the main risks?
The main risks are sensitive data, wrong context, unwanted automatic sending and workflows nobody monitors. A simple validation step reduces those risks.
Can a small business start with a simple version?
Yes. A focused workflow, a spreadsheet or CRM field and a validation step can already save time before building a larger system.
Want to frame your automation?
The AI diagnostic helps identify what can be automated, which tools should be connected and where human validation must stay.
Request an AI diagnostic