Generate Formulas with AI from Natural Language Descriptions

The most effective data transformation doesn't require formula syntax expertise—it starts with describing what you want to calculate in plain language and letting AI generate the appropriate expression.

If your formula creation is blocked by unfamiliar syntax, complex expression requirements, or uncertainty about how to reference fields correctly, you're missing the analysis capabilities that calculated fields provide. That's why analysts ask: can we create formulas by just describing what we want to calculate instead of learning formula syntax?

With Atlas, you can generate formulas using AI from natural language descriptions. No formula syntax memorization, no trial-and-error expression building, no barriers between your calculation goals and working formulas. Everything starts with describing what you want and letting AI create the formula.

Here's how to set it up step by step.

Why AI Formula Generation Matters for Data Analysis

Creating formulas from descriptions enables better data transformation for users who understand their data but not formula syntax.

So AI formula generation isn't just convenient—it's essential capability that makes data transformation accessible to everyone working with geographic data.

Step 1: Understand What AI Formula Generation Can Do

Atlas makes it easy to create formulas by understanding AI capabilities:

Mathematical calculations computing values from numeric columns (sums, averages, ratios)
Text manipulation concatenating, extracting, or formatting text fields
Conditional logic creating IF/THEN expressions for classification
Date calculations computing time differences or extracting date components
Field references properly referencing your actual column names in expressions

Once you understand capabilities, you can describe calculations effectively.

Step 2: Describe Your Formula Goal Clearly

Next, write effective natural language descriptions:

You can describe formulas by:

Starting with outcome explaining what value you want to calculate ("Calculate the...")
Naming your fields referencing actual column names in your description
Specifying conditions explaining when different calculations should apply
Providing examples giving sample inputs and expected outputs when helpful
Being specific avoiding ambiguous language that could be interpreted multiple ways

Clear descriptions lead to accurate formula generation.

Also read: Complete Guide to Formulas and Calculated Fields in Maps

Step 3: Generate the Formula with AI

To create formulas from your descriptions:

Open formula creation accessing the AI formula generation interface
Enter your description typing what you want the formula to calculate
Submit for generation letting AI process your description
Review the result examining the generated formula expression
Apply if correct using the generated formula in your calculated field

AI generation creates working formulas from your natural language input.

Also read: 10 Essential Formulas for Spatial Data Analysis

Step 4: Reference Your Columns Correctly

To help AI generate accurate formulas:

Use exact field names matching column names exactly as they appear in your data
Use {field_name} syntax following the correct format for field references
Describe field types mentioning whether fields contain numbers, text, or dates
Explain relationships describing how fields relate when calculations span multiple columns
Provide context explaining what the data represents when it helps clarify intent

Correct field references ensure generated formulas work with your actual data.

Also read: Filter Map Data Using Formula Expressions

Step 5: Iterate and Refine as Needed

To improve generated formulas:

Test with sample data verifying formulas produce expected results
Refine descriptions adjusting language if initial results aren't quite right
Add specificity providing more detail when formulas are close but not exact
Review AI output learning from generated syntax for future formula creation
Build incrementally creating complex formulas step by step if needed

Iteration improves results when initial generation doesn't match intent perfectly.

Also read: Create Calculated Columns for Custom Data Classification

Step 6: Apply Generated Formulas to Your Data

Now that AI has generated your formula:

Create calculated columns using generated formulas to add new fields to your data
Configure filter expressions applying formula logic to filter your geographic data
Style by calculated values using formula results to drive map visualization
Save for reuse preserving working formulas for future application
Document your formulas recording what each formula calculates and why

Generated formulas become practical tools for ongoing data analysis.

Use Cases

AI formula generation is useful for:

Business analysts creating calculated fields without learning formula syntax
GIS specialists adding data transformation without programming expertise
Operations managers computing operational metrics from field data
Marketing teams calculating geographic performance indicators
Research teams deriving measurements from collected data

It's essential for anyone who needs calculated fields but doesn't want formula syntax to block their analysis.

Tips

Be specific about fields naming exact columns rather than describing them generically
Describe desired output explaining what the result should look like or represent
Use examples providing sample scenarios when calculations are complex
Start simple building basic formulas before attempting complex multi-condition logic
Review and learn examining generated syntax to build formula understanding over time

AI formula generation in Atlas enables calculated fields without syntax expertise.

No formula syntax required. Just describe what you want to calculate and apply the generated formula.

AI Formulas with Atlas

Effective data transformation shouldn't require syntax expertise. AI formula generation creates working expressions from plain language descriptions, making calculated fields accessible to everyone.

Atlas helps you turn calculation goals into working formulas: one platform for description, generation, and application.

Transform Descriptions into Formulas

You can:

Describe calculations in natural language without formula syntax knowledge
Generate working formulas from clear descriptions of desired outcomes
Reference your actual column names using simple field name mentions

Build Analysis Without Syntax Barriers

Atlas lets you:

Create calculated columns using AI-generated formulas
Iterate on descriptions when initial results need refinement
Learn formula patterns from seeing how AI translates descriptions

That means no more syntax-blocked analysis, and no more skipping calculations because formulas seem too complex.

Discover Better Analysis Through AI Generation

Whether you're classifying data, computing metrics, or transforming fields, Atlas helps you turn calculation concepts into working formulas.

It's AI-assisted calculation—designed for accessibility and accuracy.

Create Formulas with the Right Tools

Data transformation is valuable, but syntax can be blocking. Whether you're describing calculations, generating expressions, refining results, or applying formulas—AI assistance matters.

Atlas gives you both generation and application.

In this article, we covered how to generate formulas with AI from natural language descriptions, but that's just one of many ways Atlas helps you transform data.

From AI generation to calculated columns, formula filtering, and data classification, Atlas makes data transformation accessible for geographic analysis. All from your browser. No syntax expertise needed.

So whether you're creating your first formula or building complex calculated fields, Atlas helps you move from "description" to "working formula" faster.