Episode 22: The $600 Billion Wake-Up Call — How to Build an AI Business Case That Actually Gets Approved
Six hundred billion dollars. That's how much has been poured into AI technologies across the market, according to research from Sequoia Capital and Goldman Sachs — with essentially no measurable return on investment yet realized. Finance teams are staring at balance sheets asking: where is it? In this episode of The AI Strategy Blueprint, host Lara Wilson delivers the answer.
Drawing from Chapter 8 of the book by author John Hanby, Lara walks through the precise methodology that separates approved AI budgets from stalled science projects. It comes down to one discipline: the imperative of quantification. Can you prove — in provable dollars — that your AI investment pays off? If not, your initiative is already dead in the water.
Lara breaks down the five baseline categories every organization must document before deploying AI: Time Economics, Error Rates, Volume Metrics, Labor Economics, and Throughput Constraints. Then she introduces John Hanby's Confidence Weighting methodology — a rigorous framework that applies probability weights (High, Medium, and Low) to projected benefits, so your business case is conservative, defensible, and CFO-proof. Walk into the room voluntarily discounting your own numbers, and watch the finance team's jaw drop.
From the Time-to-Dollars Conversion formula to the Four Pillars of AI ROI — Direct Cost Reduction, Productivity Amplification, Revenue Acceleration, and Risk Mitigation — this episode gives you the full quantitative toolkit. Lara even shows how saving just five minutes per week per employee can generate a 3x return on a typical AI software license.
If you've ever struggled to translate AI enthusiasm into budget approval, this is the episode that changes everything. The question isn't whether AI works — it's whether you can prove it. Can you? Learn more at https://iternal.ai/ai-strategy-blueprint
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