You have been told to 'use AI more'. Nobody told you which of your team's tasks go to AI, which need a signature, and which stay with people.
Thinking in AI for Managers is the department head's and process owner's method: inventory the work at the right granularity, sort every task into the four groups (AI does it; AI does, people approve; AI and people together; people do it), name the binding effect before you call anything Group 2, set an autonomy level by the consequence of a wrong result, write the request to IT as what the person sees — not which vendor — run the shadow run that is never shortened, measure honestly including the number that went the wrong way, and redeploy before you hire.
The running case is Mark Sullivan's purchasing department at Oakridge Manufacturing: 212 reorders a day, twelve buyers, a register of 61 tasks, 1,120 hours a month freed and placed before anyone was hired.
After this book you will be able to:
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Seller: California Books, Miami, FL, U.S.A.
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Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condition: new. Paperback. You have been told to 'use AI more'. Nobody told you which of your team's tasks go to AI, which need a signature, and which stay with people. Thinking in AI for Managers is the department head's and process owner's method: inventory the work at the right granularity, sort every task into the four groups (AI does it; AI does, people approve; AI and people together; people do it), name the binding effect before you call anything Group 2, set an autonomy level by the consequence of a wrong result, write the request to IT as what the person sees - not which vendor - run the shadow run that is never shortened, measure honestly including the number that went the wrong way, and redeploy before you hire. The running case is Mark Sullivan's purchasing department at Oakridge Manufacturing: 212 reorders a day, twelve buyers, a register of 61 tasks, 1,120 hours a month freed and placed before anyone was hired. After this book you will be able to: Build a task inventory and classify every line into one of four groups with a written reasonSet an autonomy level per task using four questions, with a review clause that steps back automaticallyWrite a buildable request to IT: what AI does, what the person sees, what a signature means, acceptance criteriaTake a baseline before the vendor and report before/after with three numbersRun a 90-day pilot with a stop rule, cohorts and a shadow runRebuild roles from the register and hold the redeployment conversation with specificsRun the thirty-minute morning: exceptions by type, the report, rules changed - never single cases16 chapters, an inventory and classification worksheet, an autonomy rule template, a 90-day pilot plan and self-tests with answer keys. Book 3 of the Thinking in AI series. In this series: 1 The Foundations - 2 Thinking in AI for Leaders - 3 Thinking in AI for Managers - 4 Thinking in AI at Work - 5 Thinking in Agents and AI-Native Systems - 6 The AI-Native Casebook. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9798172222405
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PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9798172222405
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Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. You have been told to 'use AI more'. Nobody told you which of your team's tasks go to AI, which need a signature, and which stay with people. Thinking in AI for Managers is the department head's and process owner's method: inventory the work at the right granularity, sort every task into the four groups (AI does it; AI does, people approve; AI and people together; people do it), name the binding effect before you call anything Group 2, set an autonomy level by the consequence of a wrong result, write the request to IT as what the person sees - not which vendor - run the shadow run that is never shortened, measure honestly including the number that went the wrong way, and redeploy before you hire. The running case is Mark Sullivan's purchasing department at Oakridge Manufacturing: 212 reorders a day, twelve buyers, a register of 61 tasks, 1,120 hours a month freed and placed before anyone was hired. After this book you will be able to: Build a task inventory and classify every line into one of four groups with a written reasonSet an autonomy level per task using four questions, with a review clause that steps back automaticallyWrite a buildable request to IT: what AI does, what the person sees, what a signature means, acceptance criteriaTake a baseline before the vendor and report before/after with three numbersRun a 90-day pilot with a stop rule, cohorts and a shadow runRebuild roles from the register and hold the redeployment conversation with specificsRun the thirty-minute morning: exceptions by type, the report, rules changed - never single cases16 chapters, an inventory and classification worksheet, an autonomy rule template, a 90-day pilot plan and self-tests with answer keys. Book 3 of the Thinking in AI series. In this series: 1 The Foundations - 2 Thinking in AI for Leaders - 3 Thinking in AI for Managers - 4 Thinking in AI at Work - 5 Thinking in Agents and AI-Native Systems - 6 The AI-Native Casebook. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9798172222405
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Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Neuware - You have been told to 'use AI more'. Nobody told you which of your team's tasks go to AI, which need a signature, and which stay with people. Thinking in AI for Managers is the department head's and process owner's method: inventory the work at the right granularity, sort every task into the four groups (AI does it; AI does, people approve; AI and people together; people do it), name the binding effect before you call anything Group 2, set an autonomy level by the consequence of a wrong result, write the request to IT as what the person sees - not which vendor - run the shadow run that is never shortened, measure honestly including the number that went the wrong way, and redeploy before you hire. The running case is Mark Sullivan's purchasing department at Oakridge Manufacturing: 212 reorders a day, twelve buyers, a register of 61 tasks, 1,120 hours a month freed and placed before anyone was hired. After this book you will be able to: - Build a task inventory and classify every line into one of four groups with a written reason- Set an autonomy level per task using four questions, with a review clause that steps back automatically- Write a buildable request to IT: what AI does, what the person sees, what a signature means, acceptance criteria- Take a baseline before the vendor and report before/after with three numbers- Run a 90-day pilot with a stop rule, cohorts and a shadow run- Rebuild roles from the register and hold the redeployment conversation with specifics- Run the thirty-minute morning: exceptions by type, the report, rules changed - never single cases16 chapters, an inventory and classification worksheet, an autonomy rule template, a 90-day pilot plan and self-tests with answer keys. Book 3 of the Thinking in AI series. In this series: 1 The Foundations - 2 Thinking in AI for Leaders - 3 Thinking in AI for Managers - 4 Thinking in AI at Work - 5 Thinking in Agents and AI-Native Systems - 6 The AI-Native Casebook. Seller Inventory # 9798172222405
Quantity: 2 available