This is where AI in finance stops being interesting and starts being practical #ai #aiinfinance

I hate when AI demos stop at chat answers
Because that's not how the real value comes
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Real finance work means models, dashboards, graphs, and presentation-ready deliverables.

SAI becomes really useful when you stop asking for generic help and start asking for a specific deliverable.

With the right business context, the right format, the right design direction, and the exact problem to solve.

That is when the output starts looking close to real work. Not just ideas.

In the video below, I show you what a few well-structured prompts in Claude can build straight away:

1. 3-statement model
2. Scenario planning model
3. Inventory monitoring dashboard
4. KPI dashboard with graphs
5. PowerPoint with charts
6. Monthly cost analysis dashboard

All done in a few minutes.
That matters because finance teams do not need better chat outputs alone.

They need work they can actually use.
Something they can review, improve, present, and build on.
That is the real difference maker.

A strong prompt does not just explain the task. It explains the outcome.

Save and share this with someone who wants to use AI for real finance work.

Видео This is where AI in finance stops being interesting and starts being practical #ai #aiinfinance канала Nicolas Boucher