How To Use ChatGPT Search in a Spreadsheet (Without Hallucinations)

ChatGPT search isn't scalable. And that's a problem because most of us don't need just one answer when we build lead lists. We need hundreds.

And when I say that this is a problem, I actually mean you’ll face two big problems when you want to scale ChatGPT on 100s of spreadsheet lines:

1. It will start making things up if you upload lists to ChatGPT. This will lead you to spend hours fact-checking results.
2. Using the ChatGPT app takes forever. Researching 500 companies at 1-2 minutes per query means 16+ hours of copy-pasting.

That’s why this guide shows you how to actually run ChatGPT search on a spreadsheet, at scale, and without the copy-paste cycle, or hallucinations.

📌 Summary For Those In a Rush

This article shows how to use ChatGPT search for spreadsheets using Datablist's AI Agent.

Problem: ChatGPT search is limited to a few queries at a time, and API-based spreadsheet add-ons don't have live search capabilities.

Manual ChatGPT search takes about 1-2 minutes per query. For 100 rows, that's more than 3 hours of repetitive work with inconsistent results.

Solution: Datablist's AI Agent runs ChatGPT search on spreadsheets, completing bulk AI search tasks in minutes instead of hours.

What You'll Learn: This guide explains how ChatGPT search works, why it doesn't work with Excel add-ons, and provides a step-by-step walkthrough to scale it using Datablist.

3 Key Advantages with Datablist:

1. Runs AI search on spreadsheets with up to 100k records (per sheet)
2. Eliminates manual copy-pasting by automatically populating results
3. You’ll find many resources & templates to get started easily

What This Guide Will Cover

• What ChatGPT Search Is and How It Works
• Why You Can't Use ChatGPT Search in Excel or Google Sheets
• The Step-by-Step Solution Using Datablist
• When to Use Scaled Search vs. Manual ChatGPT Search
• Frequently Asked Questions

What Is ChatGPT Search?

Before we get into the solution, let's quickly cover what ChatGPT search actually is and why it's different from regular ChatGPT.

How AI Search Works

ChatGPT isn't a search engine. It's a language model trained on data with a knowledge cutoff. Without search capabilities, it can only answer based on what it learned during training.

ChatGPT search changes this. When you enable it, ChatGPT can:

1. Browse the live internet
2. Visit actual web pages
3. Extract and summarize information in real-time

💡 Quick Fact

Even the ChatGPT web app you use daily is connected to OpenAI's API. But it has access to a lot of different "tools" that the raw API doesn't offer to third-party developers.

Search is one of those tools.

The Benefits

Using ChatGPT search gives you a few clear advantages over traditional search engines:

• It searches with your context. You don't need to craft the perfect Google query. Just describe what you're looking for in plain language, and it figures out what to search.
• It extracts information for you. Instead of opening 10 tabs and scanning articles, ChatGPT search reads the pages and pulls out exactly what you need.
• You can instruct it to check specific sources. Want it to only look at LinkedIn, Crunchbase, or company websites? Just tell it.

The Downsides

As useful as ChatGPT search is, it has real limitations that make it frustrating for anyone working on serious projects:

↳ One query at a time

↳↳ No way to run it on a spreadsheet natively

↳↳↳ A lot of hallucinations expressed with confidence

For a quick one-off question, these aren't dealbreakers. But if you need to research 100, 500, or 1,000 records? Manual ChatGPT search becomes a full-time job.

And the hallucination problem gets worse at scale. When you're copy-pasting results manually, you can't easily verify accuracy across hundreds of rows. Bad data slips through.

Why You Can't Use ChatGPT Search With Excel Add-Ons

Every spreadsheet AI add-on you've seen connects to OpenAI's API.

The problem? The API doesn't include live search capabilities. These add-ons can process text, generate content, and clean data, but they cannot browse the web.

That's why results often feel outdated or made up.

The Solution: Using ChatGPT Search on a Spreadsheet

If you need to run ChatGPT search on Excel data or Google Sheets, the workaround isn't another add-on. It's using a tool built specifically for bulk AI search, such as Datablist.com

What Is Datablist.com?

Datablist is a platform for building lead generation workflows that allows 26.000 users to find, enrich, and clean data using over 60 different tools from AI Agents to Email Finders, AI processors, Technology enrichments, and more, but the one that matters here is the AI Research Agent.

Think of it as ChatGPT search that runs on a spreadsheet. You give it a prompt, map your inputs (like company names, URLs, etc), and it executes the same search query across every row automatically.

The benefits:

• No copy-pasting required
• Runs on lists up to 100k records
• Built for automation & data enrichment
• Consistent outputs on every row (if you specify the format)
• Provides confidence scores so you know which results to trust
• Uses multiple tools (web scraping, pagination, API calls) beyond just the LLM
• … and many, many more

💡 The Difference Between AI Search in ChatGPT vs. Datablist

ChatGPT search in the app treats each conversation as one task. Datablist's AI Agent treats each row as a separate task. This means no context bleeding between records, which is what causes hallucinations when you try to batch queries manually.

Step-by-Step: Using ChatGPT Search for Spreadsheets

Here's exactly how to set up bulk AI search on your data.

When It's Useful:

• You want to enrich leads with data that isn't available in static databases
• You need to research hundreds of records without copy-pasting from ChatGPT
• You have a list of companies and need to find specific information about each one

Step 1: Sign Up and Upload Your Data

1. Sign up for Datablist

2. Upload your CSV or Excel file

Step 2: Navigate to the AI Agent

1. Click on Enrich in the top menu

2. Go to the AI Section and select the AI Agent

Step 3: Set Up Your Prompt and Map Your Inputs

1. Write a good prompt. For example: "Find the latest funding round for this company, including the amount raised and the date. The output format should be…"

Here’s a guide that shows how to actually prompt an AI research agent 👈🏽

2. Map your input column by typing / and selecting the column that contains your search subjects (company names, URLs, etc.)

Step 4: Configure Your Outputs & Settings

1. Once you’ve written your prompt and mapped your properties to it, scroll down and create your *Output Properties. *You can create as many as you want

2. After creating your outputs, scroll down and click the box next to Advanced Settings

These settings allow you to:

• Choose another LLM model
• Set the number of Maximum Iterations
• Enable the Website Scraper: Render HTML option

We recommend keeping the default LLM (GPT 4-o mini) as it is the best for this kind of task, and enabling the Website Scraper: Render HTML option, since it gives the AI agent the ability to extract data from JavaScript-Rendered websites

Once you have done this, click on Continue to Outputs Configuration

3. Add your outputs to your collection by clicking the ⊕ icons

Then click Continue with Instant Run

Step 5: Configure Run Settings

Finally, configure your run settings by clicking on the Chevron on the right side of the button. This will allow you to choose between the following options:

• Run on first 10 items: Good for checking results before committing
• Run on first 100 items: Useful if you want to validate larger samples
• Run on first {X} items: Lets you choose how many items you want to process
• Run on all view items: Process your entire list (or view if you’ve enabled filters)

Step 6: Run and Review

1. Once you have chosen your preferred option, click Run on all items

2. Review your results. Each row includes a confidence score, so you can quickly spot any results that need manual verification

When to Use This vs. Manual ChatGPT Search

Bulk AI search isn't always necessary, sometimes the regular ChatGPT search is enough. Here’s my recommendation of when to use the manual vs. scaled AI search:

Use manual ChatGPT search when:

• You have just a handful of records
• You need a conversational back-and-forth to refine results
• The research is highly nuanced and needs human judgment at every step

Use Datablist when:

• You have 10+ records that need the same research and output type
• You want consistent, structured outputs across all rows
• Time savings matter (even 50 queries would take over 2 hours manually)
• You need confidence scores to validate accuracy at scale
• You need the answer to be split into multiple columns

👉🏽 Learn here how to use AI search to find websites from a company name

The Bottom Line: ChatGPT Search at Scale Is Possible

Using ChatGPT search on a spreadsheet is easier than you think. You just need an AI spreadsheet that actually supports it (like Datablist).

The standard approach of manually querying ChatGPT and copy-pasting results doesn't scale. Excel and Google Sheets add-ons don't help either because the API doesn't include search.

Datablist solves this by letting you run AI search directly on your Excel, which has the following benefits:

• No copy-pasting
• Real-time web results for every row
• Confidence scores to catch bad data
• Hours saved on repetitive research
• … and many more

So if you've been looking for a way to run ChatGPT search for Excel data or bulk AI search on any spreadsheet, this is it.

Frequently Asked Questions (FAQ)

How Long Does It Take to Run ChatGPT Search on 100 Rows?

With Datablist is takes typically 1-3 minutes, depending on task complexity. Simple searches (like finding a company's website) run faster than multi-step tasks (like extracting multiple data points from different pages). Manual ChatGPT search would take approximately hours for the same 100 rows.

How Much Does Scaling ChatGPT Search Cost?

Datablist pricing is based on task complexity, not a flat fee. Simple searches cost fewer credits than multi-step research tasks. Plans start at $25/month, which includes 5,000 free credits. You can also purchase one-time credit packages if you run out.

Are There Rate Limits When Scaling ChatGPT Search?

Datablist handles rate limiting automatically. The AI Agent manages request pacing to avoid errors, so you don't need to worry about hitting limits or getting blocked. Just make sure you have enough credits, which you can top up anytime.

Can I Use ChatGPT Search on Thousands of Rows?

Yes. Datablist's AI Agent can run on lists up to 100,000 records per sheet. Each row is treated as a separate search task, which prevents context bleeding and reduces hallucinations compared to trying to batch queries in a single ChatGPT conversation.

Can I Use ChatGPT Search Directly in Excel or Google Sheets?

No. Excel and Google Sheets AI add-ons connect to OpenAI's API, which doesn't include live AI search capabilities. That's why those tools can process text but can't browse the web. To run ChatGPT-style search on spreadsheet data, you need a tool like Datablist that's built for it.

What's the Best Way to Automate Web Research on a Spreadsheet?

The most effective method is using an AI spreadsheet with ChatGPT-search-style capabilities, such as Datablist. It can browse the web, extract data, and populate results directly into your spreadsheet. Unlike static AI processors, Datablist’s AI search search agent can visit pages, handle pagination, and adapt to different website structures.

Is There a Way to Run AI Search on Multiple Rows at Once?

Yes. Datablist's AI Agent runs the same search prompt across all rows in your dataset simultaneously. You write the prompt once, map your input column, and the agent executes it for every record. Results populate automatically without any manual intervention.

How Can I Avoid Hallucinations When Using AI for Research?

Three things help:

1. Use specific, well-structured prompts that tell the AI exactly what to find and where.
2. Use a tool that treats each row as a separate search context, preventing information from bleeding between records.
3. Review confidence scores, which Datablist provides for every result, to quickly identify outputs that need verification.