AI tools are changing how finance teams approach financial modelling.
For growth-stage businesses, tools like Claude can speed up analysis, reduce manual spreadsheet work and improve forecasting. But the best results rarely come from asking AI to build a full model from scratch.
They come when AI is combined with experienced finance professionals who know what a good model should look like.
At InfiniteCFO, our specialist FP&A team has built and reviewed financial models for growth-stage companies across fundraising, forecasting, board reporting, strategic planning and transaction support.
That experience matters because financial modelling is not just about formulas. It is about understanding how a business works, what drives performance, how investors will interrogate the numbers and how finance can support better decisions.
A large part of modelling happens before the spreadsheet is built. It involves understanding the business, identifying growth drivers, reviewing historical performance, testing assumptions and deciding how the model should support decision-making.
Claude can accelerate mechanical and analytical tasks, but it still depends on strong commercial understanding. The better the assumptions, structure and prompts, the better the output.
One misconception about AI modelling tools is that the goal is fully automated model generation.
In practice, Claude is usually most valuable when used to improve, adapt or interrogate an existing model structure.
Experienced finance teams often work from templates already tested through fundraising, board reporting, debt processes or transactions. Claude can then help with:
This keeps the model commercially grounded while using AI to improve speed and efficiency.
The quality of AI output depends heavily on the quality of the prompt. Broad prompts often produce weak results. Specific, staged prompts work better.
For example, Claude can help turn customer-level revenue data into an MRR snowball analysis, identifying new revenue, expansion, churn and net revenue retention trends.
The best results usually come from breaking the work into stages:
Each step can be reviewed before moving on.
AI tools can produce outputs that look reasonable but do not hold up under commercial scrutiny.
Claude may misinterpret revenue movements, apply the wrong logic, overlook edge cases or miss important context. That matters when models are used for fundraising, board reporting, debt applications, investor updates, M&A or strategic decision-making.
AI can help you reach a better first draft faster. But it cannot take responsibility for the final answer.
The reviewer still needs to understand the business, the assumptions and the standard expected by investors, lenders or the board.
Finance teams need to think carefully about security and confidentiality.
Many AI spreadsheet tools involve uploading files into cloud environments. That creates considerations for scaling businesses handling sensitive financial data, customer information or investor materials.
Before using AI in finance workflows, teams should understand where data is stored, how long it is retained, who can access it and what approvals are required.
AI should make finance teams more efficient, but not at the expense of governance.
The best use of AI in financial modelling is not to replace finance professionals. It is to increase the capacity of strong finance teams.
That matters for growth-stage businesses. Financial pressure often builds before the company is ready to hire a large internal finance team. Reporting becomes more complex, investors ask sharper questions and leadership teams need faster insight.
Claude can support analysis, reporting, scenario planning, variance analysis and model iteration. But commercial judgement, investor readiness and decision support remain core CFO and FP&A responsibilities.
AI tools like Claude are becoming increasingly useful in financial modelling and FP&A workflows.
Used properly, they can help businesses move faster, reduce manual work and improve reporting and forecasting.
But the companies that benefit most will not be the ones trying to automate finance entirely.
They will combine technology with experienced finance leadership, strong commercial judgement and investor-grade financial oversight.
At InfiniteCFO, we help ambitious businesses build scalable finance functions, improve financial visibility and support better decision-making as they grow. Our CFO-led model gives leadership teams the finance capability they need without building a large internal team too early.
If your finance function is struggling to keep pace with growth, or you are exploring how AI can improve your finance processes, we would be happy to discuss how we can help.
