The case for improving your math skills in the age of AI

Business leaders cannot outsource mathematical thinking to AI without sacrificing judgment, because real-world business problems require practical, approximate thinking rather than flawless textbook solutions. Using examples from technology, finance, and decision science, the article shows why leaders must learn to check models for accuracy, think probabilistically, and distinguish sound decisions from noisy results. It also explains how nonlinear dynamics and intelligent “stakes” influence long-term outcomes – making the mastery of mathematics a key leadership competency in the AI ​​age.