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The Enterprise AI Playbook
A Practical Guide for Leaders Adopting AI Without Wasting Money or Compromising Data
21 chapters across six parts covering everything from where to start and how to measure ROI, through data strategy and model selection, to governance, ethics, and infrastructure scaling. Each chapter stands alone so leaders can jump to their most pressing question.
The hardest part of AI adoption isn't the technology — it's getting people to change how they work.
Read on Amazon →95%of AI pilots fail to reach production70%of AI value comes from people & process, not tech84%of orgs have not redesigned jobs around AI21standalone chapters — jump to your most pressing question§ Contents — 6 Parts, 21 ChaptersPart I: Foundation
- Where to Start
- Your Organization on AI
- The Spectrum of AI Use
Part II: People and Process
- Worker Skillsets
- AI Center of Excellence
- Change Management
Part III: Data and Models
- Customized Datasets for AI
- Fine-Tuned Models
- Private Data
- Graph Databases
- Vector Infrastructure
- Fine-Tuning Paths
Part IV: Economics and Evaluation
- Monetizing AI
- Token Budgets
- Measuring ROI
- Evaluating AI
Part V: Governance and Responsibility
- AI Governance
- AI Ethics in the Enterprise
Part VI: Infrastructure
- LLMOps
- The GPU Decision
- Scaling AI Workloads
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Enterprise AI Economics
What AI Actually Costs, How to Budget for It, and How to Measure the Returns
18 chapters plus four appendices delivering a data-driven framework for AI spending decisions. Covers token economics, transformation costs, buy/build/rent trade-offs, ROI quantification, governance, energy costs, and a complete economics playbook with assessment tools, decision matrices, and budget templates.
88% adoption and 15% value capture. The gap between universal deployment and measurable returns is not closing — it's widening.
$2.5TGlobal enterprise AI spending by 2026280×Decline in per-token costs since late 20225–10×Cost multiplier from pilot to production42%of orgs abandoned most AI projects in 2025Assessment Tools Decision Matrices Budget Templates Checklists Case StudiesRead on Amazon →§ Contents — 6 Parts, 18 Chapters + 4 AppendicesPart I: The New Economics of AI
- The $2.5 Trillion Question
- The Adoption-Value Gap
Part II: What AI Actually Costs
- Token Economics and Infrastructure
- Fine-Tuning, RAG, and Optimization
- The True Cost of Transformation
- Organizing the AI Workforce
- Realistic Budgeting Frameworks
Part III: Strategic Decisions
- Buy, Build, or Rent
- The Spectrum of Adoption
Part IV: Capturing and Measuring Value
- Monetizing Products with AI
- Quantifying ROI
- Beyond Cost Savings
- A/B Testing AI
Part V: The Costs You're Probably Missing
- Governance and Compliance
- Energy, Sustainability, and Sovereign AI
- Technical Debt, Agents, and the Future
Part VI: The Playbook
- AI Economics Playbook
- The Next Five Years
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The AI-Amplified Organization
How Work Changes When Machines Become Colleagues — A practical guide for leaders redesigning roles, teams, and careers in the age of AI agents
14 chapters across five parts delivering a research-backed blueprint for workforce transformation. Covers the data behind workforce compression, the new economics of AI-augmented talent, how to design hybrid human-agent teams, the leadership architecture required, and concrete 90-day, 12-month, and 36-month execution roadmaps. Written for CHROs, COOs, and CEOs leading the organizational side of AI adoption.
The organizations that thrive won't be the ones that replaced the most people — they'll be the ones that redesigned work itself.
10 → 3Knowledge-function compression ratio$2.9TUS potential by 203028–56%AI skills wage premium70–92%Savings: reskilling vs. replacementWorkforce Transformation Simulator Agent-to-Human Ratio Calculator Role Transformation Canvas§ Contents — 5 Parts, 14 Chapters + EpiloguePart I: The Great Compression
- Ch 1: The Workforce Is Already Shrinking
- Ch 2: What the Data Actually Says
- Ch 3: The $2.9 Trillion Question
Part II: The New Economics of Talent
- Ch 4: Tokens Are the New Equity
- Ch 5: The AI Skills Premium
- Ch 6: The Reskilling Imperative
Part III: Designing the Hybrid Workforce
- Ch 7: The Cybernetic Teammate
- Ch 8: The Human-Agent Ratio
- Ch 9: Three Models for Organizing AI
Part IV: The Leadership Architecture
- Ch 10: The Rise of the CAIO
- Ch 11: Champions, Not Mandates
Part V: The Amplified Organization in Practice
- Ch 12: The 90-Day Sprint
- Ch 13: The 12-Month Transformation
- Ch 14: The 36-Month Horizon
Epilogue
- A Letter to the 79%
§ 01 — CompleteBefore You Buy the RobotPrepare — CTO / CIO§ 02 — CompleteEnterprise AI EconomicsBudget — CFO§ 03 — ForthcomingThe AI-Amplified OrganizationTransform — CHRO / COO / CEO