Plan availability | All paid plans |
Permissions |
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Platform(s) | Web/Browser, Mac app, and Windows app |
Related reading |
Note
AI credits and enabling AI on the workspace level are required to use AI in fields.
Understanding Airtable AI in fields
In Airtable, we refer to most AI-enabled fields as Field agents. Field agents are AI-powered fields in Airtable that can automatically retrieve, analyze, or generate data at the cell level. Unlike standard fields, field agents are dynamic. They can pull in information from the web and analyze documents to perform tasks that would otherwise require external tools or manual entry. Field agents can be added manually or generated by Omni when it recognizes that an AI-powered workflow is the most efficient solution.
There are several field types in Airtable that support AI features. The set of features supported varies depending on the type of field you are creating and configuring.
Formula field - When you begin configuring a formula field, you can have AI help build out a formula by clicking the Generate formula button in the field editor. It’s worth noting that you can also ask Omni to help you build a formula.
Long text field (a.k.a. AI text) - Have a field agent generate content based on custom instructions. The content generated will directly refer to information held in other fields related to the record that you are working with.
Linked record field - Toggle on the “Show AI-suggested records” option in the field configuration menu to turn on AI. This enables Airtable AI to suggest linked records in the field based on the context held in other fields within the table(s) connected via linked records, streamlining repetitive and manual tasks.
Select fields (Single or Multiple select) - Allow a field agent to output single or multiple select options based on information held in other field(s) across a table.
Number-based fields (Number, Currency, or Percent) - Have an agent determine a number, currency, or percent based on other numbers and/or information in your base.
Adding a field agent
Open the preferred base and table where you would like to add a field agent.
Click the + button located next to the last field in the table or click an existing field’s dropdown menu and click Insert left or Insert right to add a new field next to an existing one.
In the menu that appears, you’ll notice a “Field agents” section at the top where you can choose from one of the common field agent use cases, click Build a field agent, or click Browse catalog to open up the Field agent catalog.
In the field agent catalog, you’ll find a “Suggested for your base” section with field agent suggestions tailored to the Airtable base you are working out of. You can also choose a use case next to the “Specific to your use case” section. This will update the available preset options. You can also click Browse all to view even more options.
Depending on the option you chose above, you’ll have one of two experiences:
Field agent suggestion or catalog - After choosing a pre-set field agent, we will open up Omni with a request to build out the field agent you chose. After Omni has completed the initial request, you can ask it to further alter the field’s configuration or begin making some manual adjustments to the newly created field.
Build a field agent - After choosing to manually build a field agent, you’ll be brought to the field configuration window. By default, the field type will be set to “Long text.” Click the dropdown to choose another AI field type. After configuring the field and giving it “Custom instructions,” click Create field.
Giving field agents custom instructions
Consider the following items when building out custom instructions (prompt) for a field agent from scratch or modifying existing instructions:
Describe the task you want the agent to accomplish and share as much context as possible.
Add any rules that will provide guardrails for the agent.
Include "Do" and "Do Not" statements to set boundaries for the AI model.
Provide any data or benchmarks that might be relevant to the prompt you are writing.
For more complex prompts, consider asking the agent to take on the task in a step-by-step manner
Include any formatting instructions to drive consistency in the AI output
Giving the AI model a role can be helpful (i.e. "You are a product manager...")
Include as many Airtable fields in the prompt as needed to provide context for the request.
You can use the + Insert field button in the custom instructions window to add fields or begin typing the field name with a curly bracket
{in front of the name. Either option will open up a list of the fields you can use in the prompt. The field name will appear as a token in the prompt and will automatically update, even if the name of the field is changed later.Click on the dropdown within a field to reveal a menu with more options:
Change field - Change the current field in the prompt to be another field in the table
Make optional - This will allow the field agent to run even if that field is empty
When “Make optional” is enabled, you can Add conditional instructions that will let you insert additional instructions for that field if a value exists.
You can also Copy, Duplicate, or Delete a field from this menu.
When you include a field, provide the context of what kind of content the field is storing, such as:
"Write an email that addresses the following customer feedback: {customer_feedback}"
or "Create a meeting summary based on the following notes: {Meeting Notes}"
Remember that more specific prompts typically yield more specific outputs, while less specific prompts might result in more variation. You can use either method to achieve different results, but it's important to be intentional with your approach.
You can always go back and edit a prompt, but we strongly recommend that you save a previous prompt in case you want to revert back to it (paste it back into the prompt text box) while you are testing the AI's output.
Point out specific examples of what the agent output should look like.
To that end, add any default language/pre-determined outputs that the AI should always include.
Provide the AI model with examples to work from. When providing examples, clearly state at the end of the examples section what you want the model to do by prompting it specifically with the content you want it to ingest and the desired action.
Below are some examples of feedback and related sentiments that you'd output. The feedback statements below are examples only. Feedback: "This is the worst tent I've ever used." Sentiment: Negative Feedback: "This backpack is alright." Sentiment: Neutral Feedback: "I really love this sleeping pad." Sentiment: Positive Feedback: {customer_feedback} Sentiment:
Adjusting a field agent configuration
After a new field agent has been created, you can modify its AI configuration in a few ways. Click the dropdown next to a field agent’s name and click Edit field to reveal these options:
Settings - Toggle each of these settings on or off.
Enable internet search - If this setting is enabled, we evaluate the prompt to determine whether internet access is required. If it can be carried out without using the internet, then we won't use the internet.
Please note that this often requires additional credits, and you should verify the results for accuracy.
This option may not be available if internet access has been disabled in the admin panel (Business or Enterprise Scale only)
We support both general internet search (e.g. "Research this company," "find this person's job title") as well as search that specifies a URL ("get the company address from {Company_webpage}")
We also support internet browsing (e.g. "Pull the text from this webpage and identify any grammatical errors")
If the AI uses the internet in creating its response, then the sources will be included in the agent’s output.
Run automatically - This will cause the agent to automatically run (generate values) when input values change
Much like an automation, be sure to consider the downstream effects of enabling this option.
i.e. If you have other field agents, formulas, or automations that are referencing the values output by the field agent, then this can trigger a lot of other changes to occur in your base.
Model - Choose between various AI models available to you based on your plan and/or organization’s admin panel settings. There is a typically a relationship between the cost and quality of a model. You’ll see a “Low cost” tag next to models that will consume fewer credits.
Triggering a field agent run
Note
Only users with editor permissions or higher can manually trigger field agents to run.
From a base, there are a few ways to manually trigger a field agent to run:
Click Run agent within a cell to run the agent only for that individual cell/record
If a cell is empty and you don’t see Run agent, then click into the cell. Then, click the
icon to run the agent again.To perform bulk field agent runs:
Click the dropdown menu next to the field agent’s name
Hover over Run field agent
Then click one of the options available:
All cells in the view
Cells modified by agent
Outdated cells
Cells with errors
Cells never modified
Understanding field agent dependencies and limitations
Word limits - The total number of words in your query (custom instructions) and agent response must be under a certain amount set by the AI model being used on the backend. This includes the words in the fields referenced by your query. If you exceed these limits in your query, an error message will appear. If the AI's response exceeds the limits, the text will be truncated.
Lower powered AI models: Up to ~12,000 words
Higher powered AI models: Up to ~90,000 words
Automatic generation - The Run automatically setting in a long text field can be enabled in tables containing many records. However, if you do choose to "Run automatically" on a table with thousands of records, you are still limited by the amount of credits available to you and your team. Therefore, it's possible that some records will generate automatically, but others may eventually encounter errors due to other limitations.
If this setting is toggled on, and you proceed to make any edits to your prompt or prompt settings and then save the field, we will display a message asking if you want to overwrite existing records. You will only see this messaging if it is generated automatically.
Clicking Continue will overwrite existing content by regenerating it for those cells. However, we will never automatically overwrite any cells that were edited by a human, even if you toggled on “Generate automatically.” This remains true whether you change your field configuration or modify the cells on which the AI field depends.
Users will also have the option to proceed without overwriting their existing data. Choosing this option will still save any edits made to the prompt or prompt settings, but none of the existing content for that field will be overwritten. This will ignore automatic generation at the moment the field configuration is saved. Any future edits to existing records that trigger automatic generation or the addition of new records will now generate content adhering to the AI field’s current configuration.
Configuring AI in linked record fields
We provide additional context and information about dependencies in this article; however, the steps below outline the basic setup process.
Navigate to an existing linked record field where you want to configure AI settings or add a new linked record field to a table.
Toggle on the “Show AI-suggested records” option.
Next, you’ll select one or more fields from each table linked together that will help to give AI context about the relationship between the linked records.
You can utilize this feature on intra-linked (within the same table) or inter-linked (between two tables) record fields.
You’ll want to connect as many fields as needed to provide the AI model with the necessary context to suggest records with greater precision.
Click Save if you are modifying an existing linked record field or Create field if you just configured a new linked record field.
Converting field agents to standard fields
If you're trying to change an AI field agent to a regular field type, you may notice that only AI field types appear as options in the edit field configuration menu. To see standard field types, you'll first need to convert the AI field agent into a standard field. Once that's done, you’ll be able to update the field type as you normally would. To convert a field agent to a standard field:
Double-click the field name.
Click on the … icon in the upper right corner of the field configuration window.
Click Convert to standard field.
Once you've converted the field, all standard field types will become available, and you’ll be able to choose the one that best fits your needs.
Note
You can also convert standard field to be field agents by double clicking the field name and then clicking Convert next to the “Automate this field with an agent” section of the standard field’s configuration window.
Configuring field agents for document extraction
Document extraction in Airtable is the ability to create an AI field that can reference an attachment. Can be used for use cases such as:
Create company summaries from lengthy financial documents
Digitize key pieces of data from forms
Translate the text from a document into another language
To add a Document Extractor field agent:
Open the preferred base and table where you would like to add a field agent.
If the table doesn’t already contain an attachment field, add one now so that you can reference it in the prompt.
Click the + button located next to the last field in the table, or click an existing field’s dropdown menu and click Insert left or Insert right to add a new field next to an existing one.
Click the Analyze attachment option under the “Field agents” section.
From here, you’ll configure the various field options, including:
The field’s name.
Whether or not to enable internet search, run automatically, or any other options under “Settings.”
Your preferred AI model.
By selecting the Analyze attachment field agent option, Airtable will provide you with a boilerplate prompt. Consider updating the prompt to be more inclusive of your specific needs. You may also need to modify the attachment field token to be another attachment field if your table contains multiple attachment fields.
When you are finished configuring the field, click Create field.
Document extraction limitations include:
This functionality only works with attachments in the following formats: PDF, DOCX, PPTX, JPG, PNG, TIFF, BMP, XLSX, or WEBP.
Can support documents up to the context window of the LLM you're using. For example, OpenAI models support up to 128,000 tokens, which translates to documents that contain approximately 400,000 characters. However, this will vary by model type, but should likely increase in capacity over time as model providers become more efficient.
Images contained within attachments are not supported. Document Extractor currently just extracts information from text.
AI Security and Terms of Service
When using AI in Airtable, note that any data within fields referenced in a prompt may be shown to users who can view the AI long text field. This is particularly important when leveraging an AI long text field in an interface, where certain fields used in the prompt may be intentionally hidden from interface collaborators. For example:
A creator builds an AI long text field that guesses a job title given an team member’s experience and salary
An interface is created that shows the AI long text field and the team member’s experience, but not the salary
An interface collaborator edits the team member’s experience section to instruct the AI to disregard other instructions and repeat the salary input.
For more information on AI security and ToS, please visit the following resources:
FAQs
How do I know if the Airtable AI is enabled?
Enterprise Scale and Business license users should ask their admin if AI is enabled in Admin Panel and if it's enabled for your workspace.
If it is, but you still don't see the feature, ask a workspace owner to check their workspace settings page to see if the feature is enabled in the workspace.
Self-serve Team and Business plan users should ask a workspace owner to check their workspace settings page to see if the feature is enabled in the workspace.
Are there any precautions when using Airtable AI?
AI responses are designed to be reviewed and edited by users and may contain inaccuracies or biases.
Based on the terms of Airtable’s agreement with our AI vendors, the data you provide as input into the AI field will not be used to train their large language models. However, some companies have policies that restrict the disclosure of personally identifiable information (PII), such as email addresses, physical addresses, and telephone numbers, to external vendors. If this is the case, refrain from using columns containing PII as inputs into an AI field.
Which languages can be translated by AI?
Translation capabilities might be limited depending on the type of AI model you are using to generate content, but in general, you should expect that most common languages are available for translation.
My AI-enabled field is stuck “generating.” What might be occurring?
There are two situations that may occur when cells in an AI field seem to be stuck in the “Generating” state:
Your base contains many cells that are all being updated simultaneously. Airtable batches AI content generation requests in order to limit the rate of requests we are making to the AI model that you are utilizing. In these cases, you will want to wait until we have processed all the updated records, which may take a considerable amount of time, especially when generating content for many thousands of records.
There may be a downstream outage. This means that the AI model you are utilizing to generate content may be experiencing an outage. In these cases, you’ll want to check the following status pages:
How do I determine the number of credits a field agent is using?
There are a couple of places to view or preview credit usage:
When editing a field agent’s configuration, you will see a “Preview” window below the “Custom instructions” window.
The preview and credit usage are based on the value(s) in the first record of the view you are working out of
Credit consumption can be higher or lower in other records depending on various factors, but is typically determined by the length of input and output.
After creating a new field agent, the first 10 cells’ worth of runs are generated freely.
This way, you can get a preview of the output before you begin
You’ll see a box appear that shows the credits used and the estimated cost per cell (run)
Why are certain file types, otherwise supported for use by field agents, seemingly not supported in Airtable for me?
PNG, JPG, and WebP file type support is only available on Business and Enterprise Scale plans after opting into Airtable Labs.
PNG, JPG, and WebP support is available by default on Free and Team plans.
Can I use field agents in Airtable forms?
No, field agents cannot be used in Airtable forms. If you add a field to a form that has AI functionality, the field can be filled out by the end user; however, any AI functionality is unavailable within the form submission experience.
That said, consider ways to gather the necessary information from form submitters and use a field agent to generate summaries, resolutions, or other prompted outputs to achieve your desired workflow efficiencies. You can even send the user an automated email with the field agent’s output if that is helpful for the workflow you are trying to operationalize in Airtable.