The AI Management Series - The AI-Driven Organization: The Operational Playbook for COOs and Change Leaders on Restructuring Processes, Teams, and Value Chains
Reseña del libro "The AI Management Series - The AI-Driven Organization: The Operational Playbook for COOs and Change Leaders on Restructuring Processes, Teams, and Value Chains"
In February 2024, Klarna announced that its AI assistant was doing the work of 700 full-time agents - millions of conversations resolved, resolution time cut from eleven minutes to two, $40 million in profit improvement. The numbers were real. Fifteen months later, Klarna was hiring humans back. Nothing about the AI had failed. What failed was the organization plugged into it - the org chart, the headcount math, the incentives, and the accountability lines that nobody had redesigned to hold the weight of what the technology had already changed. That is the gap The AI-Driven Organization exists to close. Not whether to adopt AI - that decision is already made, at your company and everywhere else. The question this book answers is what has to change structurally once AI is actually doing real work inside your organization: how many people a department needs, what a manager's job becomes, who's accountable when the AI costs you money, and how to redesign the operating model without ever touching a line of code. This is not a technology book, and it never asks the reader to think like an engineer. It's a field manual for the COO or change leader who owns the gap between "we have AI" and "our organization actually operates differently because of it" - written the way The Innovator's Dilemma is written, with named companies, real consequences, and frameworks built for a boardroom, not a codebase. Inside, you'll learn: Why a McDonald's AI drive-thru that mostly worked ended up adding bacon to a customer's ice cream on camera - and the one checking step every AI-touched process needs before its mistakes become public Why Salesforce's Marc Benioff cutting 9,000 support jobs to 5,000 doesn't mean your own headcount math should be simple division - and the two numbers you actually need to plan around instead Why an AI infrastructure decision made once, at low volume, quietly stops being the cheapest option as usage grows - and how one startup's public switch between AI model providers shows when to revisit it Why employee resistance to AI rarely looks like refusal - it looks like quiet sabotage and performative compliance - and the three-question credibility test that predicts whether your own rollout will trigger it Why the metrics most companies use to judge AI-assisted work actively reward employees for ignoring it - and the two-number standard that catches what volume alone hides Why "we deleted the logs" has stopped working as a defense in federal court - and the plain-record habit that makes almost any future regulatory question answerable in an afternoon instead of a multi-year discovery fight How JPMorgan Chase redesigned its operating model around AI using a disciplined, measured second ninety days - and why a company that skips straight to full deployment isn't moving faster, it's choosing not to find out what it hasn't solved yet Every case in this book is real, named, and sourced - or clearly labeled as illustrative where it isn't. Every framework is built to be used in your next executive meeting, not filed away after you finish the chapter. The AI-Driven Organization is Book 4 in The AI Management Series, which began with The AI Manager: Where Transformation Begins, Architecture & Integration, and AI Ethics, Governance, and Compliance. Read together, the series takes you from building your company's first AI team, through the technical foundation that makes AI safe to scale, through the governance floor that keeps it defensible, to the operating model redesign this book builds - before turning, in Book 5, to the one question a redesigned org chart can't answer on its own: whether the people running it are actually ready to.
