Author Description

Business Analytics in the Age of AI is designed specifically for time-constrained executives and leaders who are responsible for outcomes but may lack a background in programming or statistics. If you have ever felt the pressure to "keep up" with AI or felt sidelined by the technical jargon of data science, this book is your orientation. It is written for the professional who needs to move faster than the competition and wants to turn analytics into a practical leadership skill. Whether you lead a team in sales, operations, finance, or product, this guide is for those who want to use data to make their daily decisions more defensible and credible without becoming a full-time analyst.<br/>In the past, high-level analytics was locked behind a "specialist barrier," creating a chronic analyst bottleneck. Leaders often had to wait days or weeks for data teams to answer simple business questions, leading to "intuition-only" decisions that were vulnerable to bias and missed opportunities. This book addresses the shift from a code-based paradigm to a conversational one. It tackles the challenge of the "data explosion"—where organizations have more information than they can actually use—and solves the problem of inaccessibility by showing how Generative AI can bridge the gap between raw data and actionable executive insight.<br/>By the end of this book, you will have mastered the ability to turn data into decisions quickly, credibly, and repeatedly. You will learn the art of prompt engineering for analytics, moving from vague requests to precise, high-impact inquiries that produce reliable results. Specifically, you will be able to: Conduct interactive exploration to identify trends, compare segments, and test hypotheses in minutes rather than weeks. Identify and avoid common failure modes, such as overconfident conclusions or missing context in AI-generated reports. Bridge the gap between intuition and evidence, using data as a disciplined check on your hard-earned experien