Hey hey!

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.

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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.

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.

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

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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.

Step 2: Enable Agent mode

This can be enabled by typing “/agent” or clicking the “+” button on the chat.

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:

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.

Step 3: Naming your tool and adding description

Give it a clear name, like "Monthly License Consolidator" or “License Consolidator.”

Step 4: Activate Code Interpreter and Data Analysis

This allows analysis of data and performs mathematical computations. The recommended model is “GPT-5 Thinking”.

Step 5: Finalize and create

After ensuring setup, you can proceed to finalize and create this custom GPT.

Step 6: Deploy or share to your team

Share the custom GPT with your finance team.

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.

This transforms a tedious manual process into a highly efficient, automated workflow.

​ The Bottom Line You and your team can overcome challenges of disparate data sources and inconsistent formats by implementing two key strategies: 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. ​ ​

Your 30-minute challenge (this week): Pick one data source. Build a simple consolidation model, either a detailed prompt for an AI agent or a reusable Custom GPT. Use it in your next data review. 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. ​Watch it now!