Your next automation purchase could solve the wrong problem. Do you know which one you actually have? A manufacturer spends heavily on a robotic arm to fix what was actually a detection problem. A distribution company spends a year on smarter software for a bottleneck that was always physical. Neither system malfunctioned. Both companies simply answered the wrong question before spending the money, in opposite directions. Physical AI vs. Data AI is Book Three in the AI for Non-Tech Leaders series, built for the same non-technical readers as the first two: CEOs, plant heads, operations leaders, and anyone facing a capital decision about where AI actually belongs in their business, software or a physical system. This book gives you a plain-English way to tell the two apart before either mistake costs you money. Drawing on three decades inside some of the world's largest technology and infrastructure companies, author Alan Renshaw walks through four questions that determine whether a proposed AI investment, robotic or software, is actually worth the capital: what kind of problem you really have, what failure would cost, what true ownership actually costs beyond the purchase price, and whether you can test it cheaply before you commit. Inside, you'll learn: The plain-English test for telling a decision problem from a physical one, before you spend a dollarWhy a vendor's purchase price is never the true cost of a physical automation investmentThe humanoid robot trap: how an impressive demo can win a budget fight it shouldn'tWhat to ask any automation vendor before committing real capitalA complete, tear-out-ready capital audit built around four questions>No jargon, no code: just four questions before your next AI dollar moves.
