A Finance Exec’s AI Transformation: From 2-Week Models to 2 Hours

I spoke to the Head of Finance for a Series B tech startup yesterday. He did a full AI show-and-tell and by the end it felt like he was going to bust through the screen like the Kool-Aid man. Here are some highlights from the call.

Financial Modeling

The first problem he attacked with AI was building a financial operating model for investors to raise their next round of funding.

His process: Uploaded data room context from previous fundraise, had Claude ask clarifying questions, then iteratively built ARR waterfall and expense budget.

He said he finished the model in 2 hours vs 1-2 weeks without AI. When I asked him about hallucination, his response was “once, and I don’t think it was the model’s fault.”

Customer ROI

The next problem he tackled was on the customer success side. This company sells into large institutions, and “what’s the ROI” is constantly discussed on customer calls.

He built a dashboard for clients that tracks incremental revenue (reported by customers), contract cost, and other important ROI metrics. He also made an internal version of this dashboard that notifies customer success when ROI dips below a certain threshold.

He took the ROI dashboard one step further and added a function that exports key metrics and charts from a customer’s dashboard into a brand-aligned QBR deck that is comprehensive and editable. If you’re looking for more practical applications like this, check out these high ROI AI use cases by category.

The AI Stack

He brought up this concept of the AI stack I can’t stop thinking about.

Traditionally, when you hire an executive, you don’t just hire them for their qualifications. You also hire them for their network, playbooks, and vendor preferences.

The same thing will happen for ALL employees. When you hire someone in the future, you’ll hire them for their AI stack (their internal tools, workflows, and skills), which gives them leverage and edge.

Month-End Close

He believes the painstaking task of month end close for a company’s financials can be taken from 10 days to 1 day with the right AI systems.

Engineers Everywhere

Every knowledge worker is turning into an engineer, and the way every knowledge worker approaches their work will look like the software lifecycle.

This guy talked about his approach to building financial models with Claude, and it sounded exactly how my engineers build software:

Context dump → PRD → master plan → orchestrate/execute → iterate

Audit Everything

The best way to rebuild your company processes to be AI-native is NOT to ask employees for problems. It’s audit everything they do.

Sit behind them as they work. Take a fine tooth comb to their calendar. Have them walk you through their most common workflows.

Play offense not defense in AI-transformation. This connects to why so many companies are frustrated with AI: they’re playing defense instead of proactively auditing their processes.

Compensation System

Final project: he built a compensation management system by using Google Sheets app script macros generated by Claude Code.

Its capabilities include:

• System pulls from Rippling API and financial model for scenario planning

• Auto-generated presentation slides with compensation philosophy and individual comp details

• Creating permissioned folders for each manager with team-specific compensation documentation

• Leveling band validation (flags out-of-band compensation)

Key Takeaways

This conversation reinforced several important points about AI in finance and business operations: financial models that took weeks can now take hours, every knowledge worker is becoming an engineer, employees will be hired for their AI stack, and the key to AI transformation is auditing what people actually do rather than asking them for problems.

The companies that win will be the ones playing offense, not defense, in AI transformation. They’ll audit workflows, build internal tools, and empower their teams to work like engineers.

If you’re an exec and you’re afraid your company isn’t doing enough with AI, shoot me an email and my team will help create a list of clear AI opportunities specific to your business.