Are you right now busy with your budget 2026?
What about if I can find you 2 hours more in your day?
Check the use case below with all the steps and you will learn how use AI to make my 2 hour Excel work in just 5 minutes.
If you prefer to watch the video where I explain all of this, you can also click here.
Enjoy!
Nicolas
Automating Data Preparation & Consolidation
We often struggle with consolidating data from disparate sources.
Let’s take my example of combining license usage reports from different departments, each in a unique format. This tedious manual task is a prime candidate for AI-driven automation.
Here is how my data looks like where each tab is different (different headers, content).
Look already at how the first 2 tabs are different and imagine all the other 10 departments doing it their own way.
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This is a nightmare if you have to consolidate all of this to have an overview.
And simply uploading a multi-tabbed file, and asking an AI to “consolidate it” will fail.
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As you can see, output is not as expected. The AI will likely stack the data without understanding the different headers or formats, leaving you with a useless file that still requires manual mapping.
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So here’s how you can use AI to tackle this complex problem:
Phase 1: Create a detailed consolidation prompt
Phase 2: Build a reusable automation tool
Phase 1: Creating a detailed consolidation prompt
As with analysis, a specific and goal-oriented prompt is critical. Use an advanced function like AI Agents to execute the task.
Step 1: Set the Context
You start by defining your role, problem, and your goal in form of a prompt. You can use the example below or customize it to fit your needs.
Consolidate all the tabs into one with the following information:
– Department (based on sheet name)
– Vendor/Product
– Licenses bought
– Price per unit
– Total cost
– Utilization ratio
Step 2: Enable Agent mode
This can be enabled by typing “/agent” or clicking the “+” button on the chat.
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The AI Agent will create a virtual environment to perform the data transformation, correctly mapping columns, cleaning data, and calculating new fields as requested.
Important Note: All AI-generated material should be reviewed, verified, and approved by a qualified human before being used for decision-making, publication, or distribution.
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Phase 2: Building a Reusable Automation Tool
A successful one-time consolidation is good, but the real power comes from making the process repeatable. You can create a Custom GPT to serve as a permanent, specialized tool for your team.
Step 1: Generate a system prompt
After the AI Agent successfully completes the consolidation, ask it:
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Step 2: Create a Custom GPT
After copying the detailed system prompt generated by the AI, paste it into the “Instructions” field when creating a new Custom GPT.
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Step 3: Naming your tool and adding description
Give it a clear name, like “Monthly License Consolidator” or “License Consolidator.”
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Step 4: Activate Code Interpreter and Data Analysis
This allows analysis of data and performs mathematical computations. The recommended model is “GPT-5 Thinking”.
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Step 5: Finalize and create
After ensuring setup, you can proceed to finalize and create this custom GPT.
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Step 6: Deploy or share to your team
Share the custom GPT with your finance team.
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Now, instead of writing a complex prompt each month, any team member can simply upload the new file to your “License Consolidator” GPT and receive a perfectly formatted and consolidated report in seconds.
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This transforms a tedious manual process into a highly efficient, automated workflow.
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Here’s what that means:
- Creating Detailed Consolidation Prompts: Instead of vague instructions, finance professionals should treat AI as a new team member, providing specific roles, problems, and goals.
- Building Reusable Automation Tools (Custom GPTs): To make consolidation repeatable, teams can create custom AI tools. After a successful one-time consolidation, the AI can generate a system prompt that can be saved and reused.
This allows any team member to upload new data and receive a perfectly formatted and consolidated report instantly, shifting from reactive data management to proactive, strategic decision-making.
Why this changes everything.
Data consolidation becomes instant. What if we need to combine license data from 10 departments by end of day? What does that mean for our reporting timeline?
Instead of spending hours manually merging spreadsheets, you get the consolidated data in seconds. Inconsistencies become visible.
“We can’t analyze SaaS spend accurately until we standardize vendor names across all reports. And that standardization can’t happen efficiently without an automated mapping process.”
Your AI model handles this automatically. Budget conversations get smarter.
This is about building a tool that helps you integrate and understand your data faster, so you can actually make informed decisions instead of just reacting to fragmented information.
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Your 30-minute challenge (this week):
Notice what changes: fewer delays, faster alignment, better decisions. This is the power of AI. Best, Your AI Finance Expert, Nicolas P.S. – What did you think of this approach? Hit reply and let me know if you’re planning to try this for your team (I read all replies). P.P.S. – This use case and 2 others are inside my new video.
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