Practical Applications of AI in Finance, Python and machine learning for FP&A
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Hi Reader , AI is moving from experimentation to execution inside finance teams. And over the next 30 days, I’ll be sharing daily practical AI workflows, automations, and implementation ideas specifically for Finance & FP&A leaders. Topics will include:
You can follow the daily content here. Today’s AI Tool: NotebookLM for FinanceMost finance teams are still using AI like a chatbot. That’s the wrong approach. NotebookLM is one of the most underrated AI tools for FP&A because it allows you to ground AI outputs using your own sources:
Instead of generic AI answers, you get finance-context-aware outputs with citations. Here is my full guide for you. Notebook LM for Finance - Full Guide.pdf Claude Opus 4.8 for FP&AClaude just released Opus 4.8. And this update matters for finance teams. It’s now better at flagging uncertainty, less likely to make unsupported claims and more capable for large-scale workflow execution Here’s where finance leaders can use it immediately: ✅ Variance analysis and root-cause explanations I also created an Excel file with prompts and examples to help finance teams operationalize these workflows. Here you can download it: Claude Opus 4.8 for Finance.xlsx Free Masterclass TonightMy friend Nicolas Boucher is hosting a practical session for finance leaders. In this 1-hour session, you’ll see practical, real-world use cases:
Live session details: Seats are limited. No technical background needed—just show up and see what’s possible. The future finance team will not look like today’s finance team. The leaders learning AI workflows now will have a massive advantage over the next 3 years. Thanks for reading the newsletter! Christian Martinez P.S. Want more real-world AI workflows for CFOs and FP&A teams? I post them regularly on LinkedIn, follow me here! |
Practical Applications of AI in Finance, Python and machine learning for FP&A