Hey Reader,

You don’t need a data scientist to start using AI in your finance workflow.

Smart finance teams are already tapping into GenAI to automate tedious tasks, simplify data messes, and quickly uncover key insights.

Today, I want to share 6 tactical tips you can start using right away. Imagine running cohort analyses in seconds instead of hours or surfacing critical KPIs without digging through endless dashboards.

Ready to save hours each month? Let’s dive in.

But before that, here's something you can't afford to miss...

Tactical AI Tips for Finance Teams (Live)

🗓️ Date: Thursday, April 10
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I'm inviting in a special live webinar next Thursday, April 10th sponsored by Maxio.

AI is quickly changing finance—and your workflows might never look the same. I'll share practical, easy-to-implement AI tips you can use right away to streamline your tasks and simplify your daily work.

You'll learn:

• How to automate tedious finance tasks with AI
• Simple ways to start using AI, even if you're new to it
• Quick wins for finance teams who want immediate results

Spots are limited, so don't miss out!

6 Tactical AI Tips for SaaS Finance Teams

You don’t need to be a data scientist to start using AI in your finance workflow.

Here’s how smart SaaS finance teams are putting GenAI to work—today.

#1 Use GenAI to identify your most valuable KPIs

Instead of chasing vanity metrics or drowning in dashboards, prompt an AI model with your raw data and ask:
​“What are the 10 KPIs that best represent our business health—and why?”

I’ve seen teams surface metrics like LTV/CAC by segment or trailing burn vs. cash runway in context. One CFO realized they were tracking costs in a way that buried a major margin issue. AI helped spot it in minutes.

💡 Pro tip: Pair this with a prompt like:

“What metrics would a board investor ask about if they saw this data?”

Upload your file if confidentiality isn’t an issue, or try this workaround: paste the column headers and one fake line of sample data.​
You’ll still get sharp insights.

#2: Run cohort analysis in seconds

Manual cohorting takes time—and it’s fragile.

In all my trainings, when I ask participants how long they need to build a cohort analysis, most answers fall between 2 to 8 hours.

Imagine doing it in 2 minutes?

It’s totally possible with GenAI + Python. You can feed your raw usage or revenue data and prompt AI to:

“Segment users by signup month and show retention and revenue trends by cohort.”

#3: Automate the data mess

If you are tired of spending hours doing the same repetitive work in Excel or Google Sheet, this is my best tip: you need to start using Scripts!

A script is a line of code explaining the machine what to do.
But now you don’t need to write the code anymore, let GenAI do it!

Prompt AI to write scripts in Google Script, Office Script, or VBA to clean and standardize your inputs. For example:
​“Write a script to combine all tabs and keep only column C, D, and E.”

I’ve seen members of the AI Finance Club shave hours off month-end close by turning repetitive cleanup into automated workflows.

Even if you’re not technical, tools like ChatGPT can walk you through the code in plain English—or even generate it for you.

#4: Ask AI: “What are 100 things I don’t know but should?”

Yes, literally ask this. I did this last Friday, and it was mind-blowing. It made me realize how many things I hadn’t even considered. You’ll get pure gold—stuff like:

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Drop in your financial model, business summary, or key reports and say:
​“Based on this, what are 100 strategic or operational questions I should be asking as a SaaS CFO?”

(If you can’t upload data, just describe your context—your LLM will still surface incredibly valuable questions.)

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#5: Invest in AI-native finance tools like Puzzle

Today I was chatting with a new AI Finance Club member—he manages several startups as Head of FP&A for a PE firm. He asked what tools he should be looking at.

I mentioned Puzzle and Concourse.

If you’re a startup, tools like Puzzle aren’t just automation—they’re rethinking accounting with AI at the core. It auto-categorizes transactions, flags anomalies, and even drafts journal entries. You get real-time views of the runway, burn, and margins.

It’s the leap from spreadsheet chaos to an always-on, AI-driven finance engine.

Still exporting from QuickBooks into Google Sheets? You need to check these two tools (I am not affiliated, I just think the teams and their products are really cool!).

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#6: Pull data via API—with AI as your helper

APIs aren’t just for engineers anymore.

You can ask AI to:
​“Write a Python script to pull MRR by customer from the Stripe API.”

It’ll generate, explain, and help debug the code. Need renewal data from Salesforce? Same process.

Just this week, an AI Finance Club member shared how she discovered the Salesforce API with ChatGPT’s help—and saved hours pulling critical data.

Even better: This puts control in your hands. You’re building a finance data layer that’s fast, flexible, and owned by your team—not stuck in a dev queue.

Which tip are you going to use?

Tell me by responding to this email.

Your AI Finance Coach,

Nicolas
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P.S. I'm joining a special live webinar sponsored by Maxio on April 10th at 12 PM ET, where I'll share even more tactical AI tips for SaaS finance teams. Spaces are limited, so grab your spot here:
​📌 Book your spot now!​