Python in Excel for Finance
By integrating Python In Excel, it now brings data science and advanced analytics capabilities directly into the familiar spreadsheet environment.
I test AI tools on real finance work before writing about them. Claude, ChatGPT, Copilot, Gemini, and the finance-specific tools that keep turning up in sales demos. Comparisons with a verdict at the top, plus the three tool guides below.
By integrating Python In Excel, it now brings data science and advanced analytics capabilities directly into the familiar spreadsheet environment.
In this guide, I’m going to walk you step by step through how to use Office Scripts to automate the stuff that usually drains your time and patience.
In this guide, I’m going to walk you through the Copilot tips and tricks I use to thrive during close, budget season, and reporting chaos.
In this guide, I’ll walk you step by step through the exact, easy process I use to build my finance-focused custom GPTs.
You’ll get three plug-and-play automations, a shortlist of 15 free finance automation tools worth learning, and a playbook to prove value first
Perplexity AI is not just a shiny chatbot, it’s a real-time research assistant that pulls insights from the open web and trusted sources in seconds.
An AI financial model isn’t about robots replacing analysts, it’s about automating the soul-crushing parts so we can get back to what we’re good at.
I tested seven AI tools for finance in early 2025. Three are no longer on my desk. Here is what I run today, what I dropped and why, and the test a tool has to pass before it gets near a real close.
Here’s the deal. This guide is your crash course in everything AI in FP&A, minus the fluff. AI systems are transforming the finance industry by automating tasks and providing insights. I’ll break down what AI actually is (spoiler alert—it’s not as scary as it sounds), why you should care, and how it’s shaking up the world of finance.
I’ll even throw in some real-world examples and practical steps so you can start applying this wizardry to your daily grind.
Most bad output from a model is a bad prompt wearing a confident tone. You ask for an analysis of this month’s results, you get four paragraphs that could describe any company in any month, and the temptation is to conclude the tool is not ready. The tool is fine. It was handed a question with no company in it, no comparison basis, and no idea what a good answer looks like. AI tools are only as specific as the instruction you give them. So this page is one framework, called SPARK, and it is five steps I use on every prompt that matters: set the scene, provide the task, add the background, request the output format, and keep the conversation open. Below it there…
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