Harvard Business School professor Tsedal Neeley outlines how successful AI strategy hinges on leadership literacy—not technical expertise—starting with the '30% rule' that leaders must understand enough to guide adoption meaningfully. The discussion traces AI’s evolution from narrow, task-specific systems to today’s agent-driven capabilities, emphasizing its role in prediction, automation, and dynamic decision-making. Real impact emerges not from isolated tools but from integrated flywheels: data, products, and network effects—exemplified by Rakuten’s 6.5% sales lift from AI semantic search. Crucially, AI thrives only when silos dissolve; cross-functional alignment around shared data and platforms is non-negotiable. Case studies—from beauty influencers leveraging AI heat maps to Domino’s and Moderna redefining their identities—show that value comes from augmenting people, not replacing them. Finally, measuring success requires shifting from vague ROI to outcome-based metrics: process speed, decision quality, and employee capability uplift—grounded in clarity, relevance, and iterative learning.