Lowest Price Ever! 
14-Days Money Back Guarantee
About AI in Business Explained
The honest reason most AI initiatives stall isn’t that the technology is too complicated. It’s that the people running them never get a clean answer to four questions: where AI actually fits in this business, which pilot to start with, what it really costs, and how to know it’s working. This eBook is built to answer all four, in that order, across twelve chapters and four parts.
The structure moves from the AI landscape and where value shows up, into strategy and pilot design, then rollout and governance, finishing with what AI looks like inside functions like marketing, finance, operations, and HR. Ten case studies are woven through, covering what worked at Moderna, JPMorgan, and Coca-Cola, and what failed at IBM Watson Health, Klarna, and Duolingo. The failures matter as much as the wins, and most AI content quietly leaves them out.
A dedicated chapter covers small and mid-sized businesses, because most AI advice assumes resources you don’t have. The 90-day action plan at the back gives you the phased build for your first pilot, with explicit kill criteria before you start. And the live prompt walks you through eight discovery questions about your business, then hands back a nine-section plan with current tool pricing the day you read it. That’s the part no other AI book gives you.
‘...frontrunner in delivering top-tier digital business resources...’
‘...has been making waves with its flagship product...’
‘...consistent emphasis on simplifying complex business topics...’
‘...shaping the future of digital business learning...’
‘...valuable resource in the ever-evolving world of business education...’
Table of contents 
-
Front Matter: How To Use This Book
- The Principle That Shapes Everything: Frameworks Don’t Expire, Tools Do – And Why This Book Is Built Differently From Every Other AI Book On The Market
- The Four Parts And The Four Reader Paths: Where To Start If You’re Exploring, Planning, Scaling, Or Troubleshooting
- The Live Update Prompt At The End: How This Book Stays Current After The Date It Was Printed
- The Four AI Capabilities Every Business Leader Must Understand: Predictive, Generative, Agentic, And Decision-Support
- What Changed In The Last 24 Months And Why This Book Had To Be Rewritten Before It Was Published
- The Three AI Hype Cycles Since 2010 – And The Patterns That Tell You Which Capabilities Are Real And Which Are Inflated
- The Vendor Landscape: Foundation Model Providers, Application Layer, Infrastructure, And Where The Value Actually Accrues
- How To Read AI News Critically: Separating Product Launches From Deployable Capabilities
- The Five Terms Every Leader Must Define For Their Own Organization Before Any AI Conversation Is Productive
- The Value Chain Map: The Five Domains Where AI Creates Measurable Value – Operations, Customer Experience, Decision-Making, Product Development, And Risk Management
- Separating High-Impact Use Cases From Low-Impact Ones: The Test That Works Across Every Industry
- Why Customer Service Is Overhyped As The Entry Point – And Where The Real First-Pilot Wins Actually Live
- Internal Use Cases vs. Customer-Facing Use Cases: Which One To Start With Based On Your Risk Tolerance And Data Maturity
- The Hidden Value Chain: Places AI Is Creating Disproportionate Value That Aren’t Covered In Mainstream Business Press
- The Opportunity Cost Question: What You’re Giving Up By Deploying AI In One Area Instead Of Another
- Case Study: Bayer Crop Science – AI Outside The Obvious
- The Five-Dimension Readiness Scorecard: Data Maturity, Technical Infrastructure, Organizational Culture, Talent Gaps, And Leadership Alignment
- How To Score Yourself Honestly – The Three Biases That Lead To Inflated Readiness Scores
- Why The Weakest Dimension Matters More Than The Average: The Bottleneck Principle In AI Adoption
- The Readiness Threshold: The Minimum Score Below Which AI Investment Burns Money
- How To Fix Readiness Gaps Before Any Pilot, In Priority Order
- When Low Readiness Is A Strategic Choice (Not A Weakness) And How To Operate Inside It
- The Strategic Question Every Leader Must Answer First: Is AI A Productivity Multiplier On Top Of Your Existing Operation, Or A Transformation Of How The Business Works?
- The Build vs. Buy vs. Partner Matrix: A Decision Framework Based On Company Size, Technical Capability, Budget, And Strategic Priority
- Choosing Your AI Thesis: Cost Reduction, Revenue Acceleration, Customer Experience, Or Competitive Moat – And Why Mixing Them Dilutes Execution
- The Portfolio Approach: Balancing One Transformational Bet With Three To Five Operational Pilots
- The Vendor Lock-In Question: Cost Dynamics, Switching Costs, And How To Preserve Optionality
- Case Study: Coca-Cola – The Portfolio Strategy In Practice
- Why Most AI ROI Calculations Are Wrong: The Four Hidden Cost Categories That Turn Break-Even Pilots Into Losses
- The Full Cost Stack: Software, Data Preparation, Training, Change Management, Ongoing Maintenance, And Vendor Switching Costs
- How To Value AI Outcomes That Don’t Have Direct Revenue Attribution – Productivity, Decision Quality, Risk Reduction
- Building A Business Case That Survives A CFO Review: The Three Numbers That Have To Be Defensible
- The Payback Timeline Reality: Why Most AI Pilots Take Longer To Break Even Than The Marketing Suggests
- When To Abandon A Business Case And Propose Something Different To Leadership
- Case Study: Cleveland Clinic – Measuring What Matters In A Complex Environment
- Why Most AI Pilots Fail Before They Start: Scoping Errors, Success Criteria Errors, And Team Composition Errors
- The Pilot Scoping Framework: Five Questions That Determine Whether A Pilot Is Real Or Theatre
- Success Criteria That Hold Up: How To Define What “Working” Means Before You Start, In Terms A Non-Technical Executive Can Verify
- The Failure Criteria Nobody Writes Down: How To Know When To Stop, And Why Precommitting To A Kill Switch Is The Most Important Step In The Entire Pilot
- Timeline Discipline: Why 90 Days Is The Right Window For Most Pilots, And What To Do If You Can’t Fit The Work Into That Window
- The Pilot Proposal Template: A One-Page Document That Gets Leadership Buy-In Without Overcommitting
- The Pilot Selection Rule: 5/3/1 Rule
- Case Study: Klarna – The Cost Of Skipping The Kill Switch
- Why AI Rollouts Fail At The Human Layer More Often Than At The Technical Layer
- The Three Workforce Reactions To AI: Enthusiasts, Skeptics, And The Silent Middle – And Which One Decides Whether The Rollout Succeeds
- Roles That Change, Roles That Disappear, And Roles That Emerge: The Honest Framework For Talking About AI’s Impact On Jobs
- Change Management When The Technology Itself Is Changing Weekly: How To Build Adaptable Adoption Rather Than Fixed Training Programs
- The Communication Discipline: How To Talk About AI Internally Without Creating Panic Or False Hope
- Permission To Not Automate: When Human Judgment, Relationship, Or Expertise Is The Actual Product, And AI Shouldn’t Touch It
- Case Study: Duolingo – When The Efficiency Calculation Ignores The Human Cost
- Case Study: IBM Watson Health – What The Press Release Version Of AI Hides
- The Pilot-To-Production Gap: Why Most Successful Pilots Never Become Operational Reality, And The Four Root Causes
- The AI Agent Question: When Agents Are The Right Pattern For Scaling AI, When They’re Not, And How To Deploy Them Without Losing Oversight
- Cross-Functional Governance: Who Owns AI When It Touches Every Department
- Standards, Templates, And Reusable Components: How To Scale Without Rebuilding From Scratch Every Time
- Centralization vs. Decentralization: The Trade-Off Between Speed Of Experimentation And Consistency Of Execution
- The Capability Building Block: Skills, Infrastructure, And Processes That Compound Across Multiple AI Initiatives
- Case Study: Moderna – Capability Building At Enterprise Scale
- The Four Governance Dimensions: Data Privacy, Bias Mitigation, Regulatory Awareness, And AI Policy
- The Hallucination Problem: The Most Underdiscussed Risk In Enterprise AI, And The Validation Discipline Every Team Needs To Install Before Deploying Outputs
- Building An AI Policy That’s Actually Followed: The Three Sections That Matter And The Ones That Don’t
- Regulatory Landscape: GDPR, EU AI Act, US State-Level Frameworks, And What Each Means For Cross-Border Deployment
- The Shadow AI Problem: Employees Using Personal AI Tools For Work, And How To Address It Without Killing Innovation
- Case Study: JPMorgan Chase – Governance Before Capability
- Marketing And Sales: Lead Generation, Content Production, Personalization, And The Use Cases That Actually Move Pipeline
- Customer Service And Support: Where AI Works, Where It Backfires, And The Hybrid Model That Outperforms Both Pure-AI And Pure-Human Approaches
- Operations And Supply Chain: Forecasting, Optimization, Anomaly Detection, And The AI Applications Most Worth The Implementation Effort
- Finance And Accounting: AI For Closing Books, Fraud Detection, And Forward-Looking Financial Planning
- Product Development: AI As A Research Accelerator, Prototyping Tool, And Customer-Feedback Synthesizer
- HR, Legal, And Compliance: Where AI Touches Recruitment, Performance, Contract Review, And Regulatory Monitoring – And Where It Absolutely Should Not
- Why Most AI Advice Assumes Resources That Small Businesses Don’t Have, And How To Think About AI Without An Enterprise Budget
- The Small Business AI Starting Point: Three Operational Decisions Repeated Weekly That AI Can Support Immediately
- AI For Small Business
- How To Build A Working AI Capability With No Engineering Team, No Data Scientist, And A Budget Under $500/Month
- The Five AI Tools Every Small Business Should Evaluate Before Adding Anything Else
- Customer Analytics, Content Production, And Operations Automation At Small Scale: Practical Implementations That Work Without Enterprise Infrastructure
- The Competitive Advantage SMBs Have Over Enterprises In AI Adoption – Speed Of Experimentation, Willingness To Iterate, And Short Approval Cycles
- Case Study: Mercado Libre – AI At Scale Outside The US Tech Bubble
- Case Study: Mid-Market Manufacturer – The Same Frameworks, Smaller Scale
- The Phased Approach: Days 1-30 Diagnose And Decide, Days 31-60 Design And Start, Days 61-90 Run, Measure, And Decide Go/No-Go
- Days 1-30 – The Diagnose Phase: Running Your Readiness Assessment, Mapping Your Value Chain, Identifying Your Top Three Pilot Candidates, And Choosing One
- Days 31-60 – The Design Phase: Scoping The Pilot, Defining Success And Failure Criteria, Assembling The Team, And Starting Execution
- Days 61-90 – The Measurement Phase: Tracking Against Your Criteria, Surfacing What Worked And What Didn’t, And Making The Go/No-Go Decision Honestly
- The Measurement Framework: How To Know Objectively Whether The Pilot Is Working, Before You’ve Fallen In Love With It
- The Go/No-Go Decision: How To Recognize A Real Win, A Partial Win, And A Learning Experience That Should Be Killed
- What Comes After The 90 Days: Scaling, Killing, Or Pivoting – And The Criteria For Each
- Why This Section Exists: How The Prompt Keeps The Book Current After The Date It Was Printed
- How To Use It: A Step-By-Step Walkthrough For Pasting The Prompt Into Claude Or Any Capable AI Chat, With Deep Research Enabled Where Available
- What To Expect: The Eight Discovery Questions, The Structured Nine-Section Output, And How To Act On The Recommendations You Receive
- The Full Prompt Block – Formatted For Easy Copy And Paste, With Framework Descriptions, Discovery Questions, And Required Output Structure
- How To Re-Run The Prompt Over Time As Your Business Evolves, Your Readiness Changes, Or New Tools Enter The Market
- Index Of Case Studies
- Bibliography
Chapter 1: The AI Landscape For Business Leaders
Chapter 2: Where AI Creates Real Business Value
Chapter 3: The AI Readiness Assessment
Chapter 4: Building Your AI Strategy
Chapter 5: The AI Business Case
Chapter 6: The AI Pilot Playbook
Chapter 7: AI And Your People
Chapter 8: Scaling AI Across The Organization
Chapter 9: AI Governance And Risk Management
Chapter 10: AI By Function – Department-Level Playbooks
Chapter 11: AI For Small And Mid-Sized Businesses
Chapter 12: Your 90-Day AI Action Plan
Back Matter: The Live Update Prompt
67 Products Included
All Products Special
Order our bestselling business bundle now and save a whopping $4,665 compared to buying each product separately.
Risk-free Purchase: Full refund within 14 days
Safe and Secure Checkout
This is our LOWEST PRICE EVER - don’t miss out!
Testimonials
99.5%
Exeptional feedback from our readers 
Risk-free Purchase: Full refund within 14 days
Safe and Secure Checkout
