Pressure-testing board narratives with real-time analytical feedback

Here is how you can use AI in FP&A every day.

If I’m working on 𝘃𝗮𝗿𝗶𝗮𝗻𝗰𝗲 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀, I may ask it to help me 𝗺𝗮𝗽 𝗼𝘂𝘁 𝗮 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗱𝗿𝗶𝘃𝗲𝗿 𝘁𝗿𝗲𝗲 so I can think through possible root causes before I dig into the data.

If I’m preparing for a 𝗯𝗿𝗮𝗶𝗻𝘀𝘁𝗼𝗿𝗺 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 that help me gather the right information without making the conversation feel too formal or one-sided.

If I’m reviewing a 𝗯𝘂𝗱𝗴𝗲𝘁 𝘀𝘂𝗯𝗺𝗶𝘀𝘀𝗶𝗼𝗻, I may ask it to 𝘀𝘂𝗴𝗴𝗲𝘀𝘁 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀 that help me understand risks and opportunities in the assumptions.

And if I’m 𝗽𝗿𝗲𝗽𝗮𝗿𝗶𝗻𝗴 𝗮 𝗿𝗲𝗽𝗼𝗿𝘁 or presentation, I may use it to 𝗰𝗵𝗲𝗰𝗸 𝘄𝗵𝗲𝘁𝗵𝗲𝗿 𝘁𝗵𝗲 𝘀𝘁𝗼𝗿𝘆 𝗯𝗲𝗵𝗶𝗻𝗱 𝘁𝗵𝗲 𝗻𝘂𝗺𝗯𝗲𝗿𝘀 𝗶𝘀 𝗰𝗹𝗲𝗮𝗿 enough for senior leaders.

Of course, the output still needs to be reviewed carefully.

You need to validate it against the actual data, adjust it for your business context, and decide which recommendation makes sense.

I would also be careful with confidential information. Before uploading anything sensitive into an AI tool, check your company’s policy and speak with your manager or IT team.

In this video, I walk through practical examples of 𝗵𝗼𝘄 𝗜 𝘂𝘀𝗲 𝗔𝗜 during a typical FP&A day, including 𝗽𝗿𝗼𝗺𝗽𝘁𝘀 for variance analysis, business partnering, budget reviews, reports, and board prep.

Full video here on my YouTube channel: https://lnkd.in/gm7TBVYX


-Christian Wattig

I've been using AI in my finance workflows for a while now. But about 60 days ago something shifted. The output stopped looking like AI output. The analysis was sharp, the structure was clean, and for the first time I felt comfortable putting my name on the work and sending it to senior leadership and key stakeholders. Anyone in finance knows what that bar feels like.

What used to take hours to sometimes days now takes minutes. But speed isn't the real story. The real story is depth. I'm running deep dives on problems I never had the bandwidth to go past surface-level on. Building scenario models with dozens of variables and layered sensitivities. Fully automating end-to-end reporting processes. Getting real-time analytical feedback on board narratives before they ever reach the boardroom.

But the tool isn't why it's working. The reason it's working is that I'm in it. Every day. Learning, building, breaking things and rebuilding them. Not hiring a vendor to spend six figures, build something nobody understands, and leave behind a tool nobody uses.

AI adoption in finance only works when the finance person IS the AI person. Domain expertise and tool expertise have to sit in the same chair. You can't outsource that. It's a skillset, not a software implementation.

Anthropic recently released Cowork, which lets AI work across your files and workflows autonomously. I've been pressure testing it daily, and this week I'm pushing it hard to see how far it can expand into other areas of the finance function. It feels like an arms race to stay ahead of the curve right now, and the gap between finance leaders who are learning this and those who aren't is widening by the week.

I'm a CPA with 12+ years across EY, Fortune 100 FP&A, and PE-backed operations. I've sat through a lot of vendor pitches. This is the first time the competitive advantage goes to the practitioner who learns it, not the company that sells it.

If you're in strategic finance and want to compare notes, let's connect. Getting started is the hardest part, and I'm happy to share what I've learned so far.

The tools are ready. The question is whether finance leaders are willing to get their hands dirty.