1. First Principles of AI Business Strategy
Picture two leaders who receive the same pitch: a vendor demo in which an AI assistant drafts flawless replies to customer complaints. The first leader asks, "How fast can we roll this out?" The second asks, "What happens on the replies it gets wrong, how will we know it is saving money, and who is accountable when it says something it should not?" Six months later the first leader is explaining a public apology and an unclear invoice. The second leader is presenting measured savings to the board. Neither leader wrote any code. The difference was a mental model.
This phase builds that mental model on three foundations. First, AI is probabilistic decision support, so it fails differently from ordinary software, and value depends on everything around the model. Second, the business strategist owns specific decisions (the problem, the value, the risk, the adoption) and deliberately does not own others (the code, the tuning, the configuration). Third, AWS packages AI in layers with a clear division of responsibility, and nearly every AWS-flavored question on this exam asks which layer fits and who owns what. Every later objective is a variation on these three ideas.
⚠️ Exam Trap: Many wrong answers on the AIB-C01 are technically sensible actions taken by the wrong person or at the wrong stage, such as "tune the model's hyperparameters" when the scenario asks what a business leader should do first. If an option belongs to an engineer's to-do list, be suspicious of it.
