Why AI Projects Fail & How "Real Options" Can Save Them скачать в хорошем качестве

Why AI Projects Fail & How "Real Options" Can Save Them

Most AI projects fail—not because the technology is bad, but because the financing model is broken. In this deep dive, we explore why treating AI initiatives like standard capital investments (using rigid ROI or NPV metrics) sets them up for failure before they even begin. Instead, we introduce Real Options Analysis—a powerful framework adapted from the financial markets. This approach treats AI projects not as static investments, but as a series of "options" that allow you to invest small amounts now to buy the right to scale later. It is the secret to managing high uncertainty, limiting downside risk, and capturing massive upside potential. In this video, you will learn: 🚀 The "Innovation Trap": Why standard Discounted Cash Flow (DCF) models undervalue high-potential AI projects. 💡 What are "Real Options"? A plain-English explanation of this financial concept and how it applies to tech innovation. 🛡️ Risk vs. Uncertainty: How to structure your AI portfolio to "fail fast and cheap" on bad ideas while keeping the door open for exponential wins. 📈 Practical Application: How to move from a "Big Bang" investment strategy to a phased, milestone-based approach that increases success rates. Who this is for: CIOs, CFOs, AI Product Managers, and Innovation Leaders struggling to justify AI budgets or looking for a better way to measure the value of uncertain technology initiatives.