The Future of AI

The future of artificial intelligence cannot be predicted with confidence. For investors, that is not a reason to stop thinking about it. It is a reason to think differently.

The Future of AI is an investor-focused guide to understanding artificial intelligence across the next 5, 10, 20, and 50 years-not by pretending to know what will happen, but by building a disciplined framework for investing under uncertainty.

At the heart of the book is the Evidence Ladder, which separates what is already demonstrated from what is plausible, genuinely uncertain, or highly speculative. This framework is then applied to AI infrastructure, capability progress, AGI, economic diffusion, labor markets, energy, compute, and the long-term economics of artificial intelligence.

Inside, you will learn:

• Why long-range technology predictions repeatedly fail
• How to build a falsifiable AI investment thesis
• What today's massive AI infrastructure commitments actually tell investors
• Why power, grid capacity, chips, cooling, and reliability may constrain AI growth
• Where serious experts disagree about AGI-and why
• Three scenarios for AI development through the 2030s
• Why technological success does not automatically mean investment success
• How AI investment thinking should change across 5-, 10-, 20-, and 50-year horizons
• How scenario planning, optionality, and signposts can improve investment decisions
• How valuation, downside, duration, liquidity, concentration, and permanent capital-loss risk should influence position sizing
• How to build and continuously update your own AI investment thesis

The book combines research, historical comparisons, diagrams, worked examples, counterarguments, scenario analysis, and practical investment frameworks to move beyond both AI hype and reflexive skepticism.

Written for investors, analysts, finance professionals, executives, entrepreneurs, and anyone seeking to understand the economic consequences of AI, The Future of AI asks a more useful question than simply trying to predict what comes next:

What do we actually know, how confident should we be, what could prove us wrong, and how should we invest accordingly?

Because the most valuable skill in AI investing may not be predicting the future. It may be knowing how to invest when the future cannot be predicted.