The Augmented Executive

Forthcoming · Business Leadership

The Augmented Executive

How to Lead AI Transformation in Your Organization

Dr. Xiaoyun Xu  ·  Dr. Jason Xiaotian Dou

“AI expands what you can delegate; leadership determines its purpose, permissions, and accountability.”
12
chapters
3
parts
9
decision tools
~111,000
words

The

Augmented

Executive

How to Lead AI Transformation in Your Organization

Dr. Xiaoyun Xu

&

Dr. Jason Xiaotian Dou

The Problem

It arrives as a technology choice

AI proposals are framed as decisions about tools. But their consequences extend across the business — and they show up in places the proposal never mentioned.

Fluent answers

from records that mean different things in different parts of the business.

Drafting time saved

but new review work created for someone else to absorb.

Routine tasks removed

that junior staff used to learn the job through.

These are leadership problems — requiring choices about resources and responsibility.

The Framework

The Captain’s Compass

Four questions every leader should be able to answer before AI takes on meaningful work.

What useful result does the organization seek?

Start from the customer or business outcome, not the technology. Name the result that would justify the effort and the person accountable for achieving it.

Key Ideas

Three ideas to carry into every decision

01

Whole Job Test

Follow the work from the initial request all the way to the accepted business outcome — not just the step AI performs.

02

Review Tax

The human effort required to check, correct, and finalize AI work. It is real cost, and it must be counted.

03

Junior Deficit

When routine work disappears, the practice through which people learn may disappear with it.

Capability does not by itself grant authority, and a signature does not by itself establish effective oversight.

Outcomes

What readers will be able to do

  1. 1

    Frame an AI proposal around a customer or business outcome and name the accountable person.

  2. 2

    Assess whether information and source records are fit for the specific decision.

  3. 3

    Compare complete ways of doing the work, including preparation, checking, correction, exceptions, and support.

  4. 4

    Distinguish released staff capacity from demonstrated cash saving.

  5. 5

    Design meaningful human review and preserve professional competence.

  6. 6

    Specify permitted actions, escalation, and recovery responsibilities.

  7. 7

    Translate values into funded service commitments and decision rights.

  8. 8

    Connect supplier selection and growth with evidence of customer demand, operating value, and continuing ownership.

Inside the Book

Three parts, twelve chapters

Fictional executive cases throughout the book are teaching cases, clearly labelled as such.

Part One — Setting Direction

Part Two — Designing the Operating Model

Part Three — Committing Resources

The Decision Toolkit

Nine tools for accountable decisions

#Tool
1Core decision record
2Source and readiness evidence
3Intervention record
4Workflow comparison and funding
5Employee compact and capability
6Delegated action and recovery
7Values and continuing oversight
8Portfolio and supplier decision
9Closure and handover checklist

An editable Word toolkit companion accompanies the book, so teams can put each tool to work.

Who It Is For

Written for those who own the outcome

Primary readers

Executives, business owners, business-unit leaders, and senior functional managers accountable for business outcomes.

Also valuable for

Transformation leaders, board members, advisers, and MBA and executive-education participants.

About the Authors

Meet the authors

XX

Dr. Xiaoyun Xu

Professor, Ateneo de Manila University Graduate School of Business

Holds a PhD in industrial engineering from Arizona State University and a bachelor’s degree in the same field from Tsinghua University. Previously a professor at Peking University.

His work connects data science and optimization with operations management and decisions under uncertainty, with experience across manufacturing, logistics, e-commerce, and public administration.

xxu@ateneo.edu
JD

Dr. Jason Xiaotian Dou

Founder & CEO, Marbella AI

Founded Marbella AI (marbellaai.com) with a mission to empower the next generation with AI literacy and to identify and develop future AI leaders. Marbella AI has trained more than 1,000 people.

B.S. in Computer Science, Peking University; M.S. in Information Science, Cornell University; Ph.D. in Computer Engineering, University of Pittsburgh; postdoctoral work in AI at Harvard University.

j@marbellaai.com