How To Clear Validation in Google Sheets and Excel

Why Data Validation Cleanup Becomes a Time Sink

If you only touch a single spreadsheet now and then, removing data validation is simple. But business reality looks different: shared pricing workbooks, CRM exports, agency reports for dozens of clients, all with hidden rules baked in. Multiply that by months or years, and your team quietly burns hours just trying to type into cells.

A smart workflow combines solid manual techniques for one‑off fixes with AI agents that handle the bulk cleanup at scale.

Method 1: Manual Cleanup in Excel (Great for Small Jobs)

A. Remove Validation From Selected Cells

1. Open your Excel file.
2. Select the cells you want to unlock (or press Ctrl+A to select the whole sheet).
3. Go to Data > Data Validation.
4. In the Settings tab, click Clear All.
5. Click OK.

Pros:

• Very controlled — you know exactly what you’re changing.
• No setup or code required.

Cons:

• Painful when you have many sheets or workbooks.
• Easy to miss cells still bound by old rules.

B. Find All Validation With Go To Special

1. Press Ctrl+G to open Go To.
2. Click Special…
3. Choose Data validation (All or Same).
4. Click OK to select all validated cells.
5. With those cells selected, go to Data > Data Validation > Clear All > OK.

When to use: When you inherit a messy file and want to strip every rule in one shot.

C. Use a VBA Macro for Repeated Work

If you often clean the same kind of workbook, a macro helps:

1. Press Alt+F11 to open the VBA editor.
2. Insert > Module.
3. Paste:

Sub RemoveDataValidation()
   Dim ws As Worksheet
   Dim rng As Range
   Set ws = ActiveSheet
   Set rng = ws.UsedRange
   rng.Validation.Delete
End Sub


4. Press F5 to run.

Pros:

• One‑click cleanup for large sheets.
• Reusable across files.

Cons:

• Requires macro‑friendly environment.
• Still limited to Excel on your local machine.

Method 2: Manual Cleanup in Google Sheets

A. Remove Validation From Specific Ranges

1. Open your Google Sheet.
2. Select the cells or columns that feel “locked”.
3. Click Data > Data validation.
4. In the side panel, click Remove validation.

B. Clear Validation Across a Whole Sheet

1. Press Ctrl+A (or Command+A on Mac) twice to select all cells.
2. Go to Data > Data validation.
3. Click Remove validation.

Pros:

• Simple, no scripts required.
• Works in the browser, nothing to install.

Cons:

• Still manual for every sheet and file.
• Easy to forget a tab or shared document.

Method 3: Let an AI Agent Do the Clicking For You

Manual methods break down when you’re:

• Cleaning dozens of client spreadsheets.
• Standardizing templates across teams.
• Migrating from one system to another.

This is where a computer‑use AI agent like Simular shines. Instead of writing brittle scripts, you give the agent a goal:

“Open each Excel and Google Sheets file in this folder, find all cells with data validation, remove the rules, save a log of what changed, then re‑save the files.”

Because Simular Pro can operate across your entire desktop environment, it can:

• Open Excel workbooks and Google Sheets in the browser.
• Navigate through Data > Data Validation menus exactly like a human.
• Use shortcuts (Ctrl+G, Go To Special) to find all validated cells.
• Apply consistent cleanup rules across hundreds of files.

How a Typical Agent Workflow Looks

1. Define the scope
   • Point the agent at a folder, drive, or list of links.
2. Describe the pattern
   • “In Excel: use Go To Special to find all validation, then Clear All. In Google Sheets: use Data > Data validation > Remove validation for each tab.”
3. Add safeguards
   • Ask the agent to create backups or export a CSV of changes (file name, sheet, range, rule removed).
4. Run and review
   • Because Simular emphasizes transparent execution, you can inspect the agent’s action history and tweak instructions if needed.

Pros of Using an AI Agent:

• Massive time savings when cleaning many workbooks.
• Consistent behavior across Excel, Google Sheets, and other tools.
• No need to maintain fragile macros or scripts.

Cons:

• Best suited when you have repeatable patterns, not one‑off clicks.
• Requires a short initial "onboarding" phase to describe your exact rules.

Putting It All Together

For a single messy file, manual Excel or Google Sheets steps are often enough.

But when your team lives in spreadsheets — forecasts, media plans, campaign trackers, invoices — removing data validation becomes a recurring tax on everyone’s time.

Use the manual methods as your safety net for spot fixes. Then, once you see the pattern, capture it in an AI workflow with Simular, let the agent handle the clicks, and free your team from ever hunting down stubborn validation rules again.