Financial Modeling in the Era of AI
In Mrs. Jackson’s fourth grade class, and I’m guessing each of you had your own Mrs. Jackson, I learned to do long division by hand. Three-digit numbers, four-digit numbers, the whole bit. Pencil, paper, and that little ladder of subtraction and bring-downs that took forever and felt, even as a nine-year-old, like the most inefficient possible way to divide one number by another.
Here’s what I remember thinking, and I’d bet you thought the same: why are we doing this when there’s a calculator right there?
The answer, of course, is that I needed to understand the mechanics. The inputs, the logic, how the outputs got created. Mrs. Jackson wasn’t about to hand me a calculator until she was confident I could do the thing by hand. And that process, quite frankly, was critical. I needed to understand the fundamentals before the world handed me a calculator.
The Same is True for AI and Financial Modeling
I think the same is true for AI and financial modeling.
Before you can use AI to underwrite a deal, or forecast development cash flows, or run a partnership waterfall, you’d better understand the fundamentals. Why the inputs become the outputs. That’s what we teach in our A.CRE Accelerator Core and our Advanced Endorsements. We show you how to take inputs, run them through the right series of calculations, and produce reliable outputs, and we show you why those outputs are what they are.
The medium has changed over time. It started in our heads, then on paper, then in Excel, then Argus, and increasingly now in AI. But the actual logic, the underlying math and reasoning of forecasting cash flows, doesn’t change. The fundamentals remain constant.
In the video below, you’ll see what I mean. Watch an AI Skill embedded in Claude in Excel complete the first case study in the A.CRE Accelerator. The rent roll, income and expenses, NOI, cap rate, and modeling notes, all in about two minutes.
How AI Shows Up Inside the Accelerator
We’re sitting here in the middle of 2026, and over the coming months and years, you’ll see Michael, myself, and the rest of the A.CRE team roll out more and more AI assistance, all aimed at helping you become proficient at using AI as your “calculator” for building real estate financial models from scratch.
Here’s how it’ll work. Each course will follow a standard arc:
- Learn the fundamentals through the lessons.
- Complete the case study by hand using traditional tools like Excel. This is your long division by hand.
- Watch one of us do it by hand. Michael or I will walk through the same case study. We call this the Watch Me Build.
- Receive an AI Skill (sometimes referred to as a Claude Skill).
That last piece is what’s new, so let me explain.
An AI Skill is a mechanism by which we teach an AI a specific procedure. In this case, how to complete a particular modeling task. We package the procedure up, and at your option, you load it into Claude, ChatGPT, or whichever AI tool makes the most sense for you. Then you talk with it.
Three Ways to Use an A.CRE AI Skill
Each skill we give you can do one of three things, and you choose which one at any given moment.
It can build it for you. This is what you saw in the video. The AI completing the case study end-to-end in about two minutes. If you’re using Claude in Excel or ChatGPT in Excel, you can watch it work in real time. Or you can have it work in chat and then walk you through what it did. Critically, you can interrogate every choice it made: why did you structure the rent roll that way? Why did you trend rents using that formula? How did you size the cap rate? The AI will tell you.
It can tutor you. If you don’t fully understand the mechanics of what you’ve been learning, what’s happening inside a particular calculation, why a formula is structured the way it is, how a concept fits with everything else, the skill will teach you. Just ask it questions.
It can review your work. I think this is the most powerful element. You’ll build the model by hand, then hand it to the AI and ask it to check what you’ve done. It’ll tell you whether you got it right. And if you didn’t, it’ll coach you through the fix. You can still post in the Accelerator Q&A forum, of course, but the AI is right there alongside you, twenty-four hours a day.
The Goal: AI as Your Companion in Real Estate Financial Modeling
This is the path: learn the fundamentals, watch us do it by hand, do the case study yourself by hand, then work alongside an AI that knows the procedure, sometimes as your tutor, sometimes as your reviewer, sometimes as your builder.
Over time, you’ll come to see AI in its proper role. As an assistant to multiply your output and elevate you to the work that really matters. The same way the calculator became my assistant, freeing me from the mundane to tackle the more challenging. But that day only came once Mrs. Jackson confirmed I had mastered the fundamentals.
The fundamentals first. Then the calculator. That order matters.
Welcome to financial modeling in the era of AI.
If you have any questions, comments, or want to say hello, feel free to reach out via email or LinkedIn.
Frequently Asked Questions about Financial Modeling in the Era of AI
Why fundamentals first?
Learners need to understand the fundamentals because, before using AI “to underwrite a deal, or forecast development cash flows, or run a partnership waterfall,” they must understand “why the inputs become the outputs.” The post compares this to learning long division before using a calculator: “I needed to understand the fundamentals before the world handed me a calculator.”
What stays constant?
The medium changes, but the logic does not. The post explains that modeling has moved “in our heads, then on paper, then in Excel, then Argus, and increasingly now in AI,” but “the actual logic, the underlying math and reasoning of forecasting cash flows, doesn’t change. The fundamentals remain constant.”
How does AI fit?
AI is introduced after learners build a foundation. Each course follows this arc: “Learn the fundamentals,” “Complete the case study by hand,” “Watch one of us do it by hand,” and then “Receive an AI Skill.” The AI is positioned as a companion after the learner has done the modeling work manually.
What is an AI Skill?
An AI Skill is “a mechanism by which we teach an AI a specific procedure, in this case, how to complete a particular modeling task.” The procedure is packaged so learners can load it “into Claude, ChatGPT, or whichever AI tool makes the most sense” and then interact with it.
Can AI build models?
Yes. One use of the skill is that “it can build it for you.” The post describes an AI completing the first A.CRE Accelerator case study, including “the rent roll, income and expenses, NOI, cap rate, and modeling notes,” in about two minutes.
Can learners question AI?
Yes. The learner can “interrogate every choice it made,” including questions such as “why did you structure the rent roll that way?”, “Why did you trend rents using that formula?”, and “How did you size the cap rate?” The post states that “The AI will tell you.”
How can AI tutor?
The skill can tutor learners when they do not fully understand “what’s happening inside a particular calculation, why a formula is structured the way it is, how a concept fits with everything else.” The instruction is simple: “Just ask it questions.”
How can AI review work?
The learner can build the model by hand, then “hand it to the AI and ask it to check what you’ve done.” The AI can tell the learner “whether you got it right,” and if not, “it’ll coach you through the fix.” The post calls this “the most powerful element.”
What is AI’s proper role?
AI’s proper role is as “an assistant to multiply your output and elevate you to the work that really matters.” The post compares this to a calculator becoming an assistant, “freeing me from the mundane to tackle the more challenging,” but only after the fundamentals have been mastered.
What is the learning path?
The recommended path is: “learn the fundamentals, watch us do it by hand, do the case study yourself by hand, then work alongside an AI that knows the procedure.” The AI may serve “sometimes as your tutor, sometimes as your reviewer, sometimes as your builder.”
