Turn AI Spending into Provable Business Value

If you're reading this, there's a good chance you've already sat in a room where someone presented an AI initiative with compelling slides, impressive demo metrics, and a business case that quietly fell apart the moment anyone asked a hard financial question. Maybe you were the person asking. Maybe you were the one presenting and hoping no one would.

That tension — between the genuine potential of AI and the near-total absence of rigorous financial governance around it — is exactly what this school is designed to resolve. I've spent years working at the intersection of strategy, finance, and technology, and the pattern I see repeated across organizations of every size is the same: smart people making expensive AI decisions without the measurement architecture to know whether those decisions are working. Not because they aren't capable, but because nobody handed them a theory cum praxis framework built for this specific problem.

Traditional ROI thinking wasn't designed for AI. The costs are distributed in ways that don't show up in standard capital models — data infrastructure, integration debt, compliance overhead, the ongoing talent cost of keeping a system production-ready. The benefits are real but notoriously hard to attribute cleanly. And the pace of investment decisions often outstrips any organization's ability to build measurement discipline from scratch. The result is what I call "AI by faith" — spending that gets approved because AI is strategically important, governed by hope rather than evidence.

What I've built here is the antidote to that. Not a technology course, and not a vague executive overview, but a precise, commercially grounded curriculum that gives you the tools to define the right KPIs, model the true total cost of ownership, design pilots that generate trustworthy evidence, quantify productivity gains in terms a CFO will trust, and govern a portfolio of AI investments the way any serious capital allocation deserves to be governed.

The goal isn't to make you skeptical of AI. It's to make you rigorous about it — so that when you champion an investment, you can defend it with numbers, and when you cut one, you can explain exactly why. That's not just good finance. It's how organizations build the kind of AI culture that actually compounds over time.

If you're ready to stop guessing and start governing, I'll see you inside.