Airtable AI Fields: Automate Data Enrichment with Zero Code

Airtable AI fields can help automate data enrichment without writing code. Configure them for tasks such as categorisation, translation, or summarisation, then check the results before applying the setup across your base.

Create an AI Field for Categorisation

If AI fields are available in your Airtable workspace, add one to the table and select a categorisation option.

1. Open the field menu and select the AI field option for categorisation.
2. Choose the input field, such as Description.
3. Enter your category list, such as SaaS, eCommerce, HealthTech, EdTech, Fintech.
4. Name the output field Industry.
5. Create the field and review its output.

Avoid overlapping categories. Define the decision rules clearly if the same record could fit more than one category.

Translate Contact Notes

Use a translation field for support notes, biographies, or other text that needs converting into another language.

1. Select the text field containing the original content.
2. Choose the target language.
3. Use automatic language detection if your records may contain different source languages.
4. Review the results for names, technical terms, and formatting.

Keep the original text in a separate field. This makes it easier to compare the source with the translation and correct unclear output.

Summarise Support Tickets

A summarisation field can condense long ticket descriptions into a shorter, consistent format. Give it an instruction such as:

Summarise this support ticket in two sentences, keeping the product name and error code.

Start by summarising a few representative records. Compare the output with the original ticket and revise the instruction if important details are missing or ambiguous.

Check Cost and Workflow Behaviour

Before processing a larger table, check the current pricing and usage information in your workspace. Review how field updates are counted and whether changing a source field causes the AI field to run again.

Run a small sample first and inspect:

• the field configuration;
• the generated output;
• the effect of prompt changes;
• how source edits affect the result;
• which usage details your workspace displays.

Do not assume that speed, cost, or accuracy will remain the same across different tasks or inputs.

Refine Outputs with Prompt Changes

Write a short classification guide in the field instructions. For example:

Use the most specific matching category. If the information is unclear, choose General SaaS.

Add examples of records and desired outputs when the interface allows it. Test the instruction on varied records, inspect the results, and revise the wording.

For translation, include relevant guidance such as:

If the source contains mixed English and Spanish, translate the full record into Spanish.

Avoid instructions that conflict with one another. Split complex tasks into separate fields when each part needs a different prompt or review process.

Connect AI Fields to Automations

Use an Airtable automation to act when an AI field produces or updates a value. The automation can update another field, send a notification, or route a record for review.

For lead routing, create a condition based on the Industry field. If it equals Fintech, update the record’s status or send a notification to the appropriate person.

Before enabling the automation for your full table:

1. Add AI fields for classification, translation, or summarisation.
2. Configure the output field and prompt.
3. Review the results on sample records.
4. Add conditions for the required action.
5. Test the workflow with a suitable record.
6. Monitor the records that meet the trigger condition.

Keep tools such as Zapier in mind as possible connectors, but check which actions your workflow requires and confirm compatibility before setting them up.