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Digital Transformation with AI Big Book
Digital Transformation with AI Big Book is a field-tested playbook for moving large organizations from technology upgrades to intelligence-led operating models. The book argues that competitive advantage now comes from reducing decision latency—how quickly and safely a company senses, decides, and acts—and shows how to achieve this using governed data, platforms, and AI (including agentic patterns) within an evidence-based operating model.
The narrative follows a lifecycle leaders can run Vision & Value → Portfolio & Governance → Target Architectures → Data/AI & MLOps → Build & Integrate → Pilot & Hypercare → Scale & Localize → Operate & Optimize. Each stage provides decision guides, reference patterns, checklists, and 30-60-90 day plans, allowing boards and executives to fund by outcomes, de-risk delivery, and prove benefits.
Vision & Value defines where to win now, framing a small set of measurable bets tied to customer moments, productivity, or risk reduction.
Portfolio & Governance replaces project thinking with persistent product teams, outcome-based funding, and a light but firm stage-gate.
Target Architectures set “clean-core ERP/CRM, smart edges” with API/event integration, zero-trust security, observability, and quality attributes.
Data Products, AI & MLOps turns data into governed products and establishes model pipelines, evaluation, and drift/safety controls.
Build & Integrate details the DevSecOps backbone, API engineering, event meshes, testing, and reversible release practices.
Pilot & Hypercare shows how to prove value with bounded scope, strict go/no-go criteria, and day-one telemetry.
Scale & Localize introduces release trains, localization packs, multi-region patterns, and decommissioning so value lands on the P&L.
Operate & Optimize aligns SRE, FinOps/GreenOps, and a Value Realization Office to run for reliability, cost, and benefits—not just uptime.
Platforms & Ecosystems offers pragmatic guidance across ERP/CRM, data/AI stacks, ServiceNow, and integration fabric.
A Strategy–Lifecycle–Software Matrix links strategies, phases, tools, and KPIs on one page for quarterly steering.
Industry Playbooks (manufacturing, BFSI, healthcare, public sector, etc.) provide first bets, metrics, and risks by sector.
The Human Enterprise covers change, skills, ethics, accessibility, and adoption—treating capability building as a product.
Future Horizon looks at agentic AI, multi-agent systems, digital twins, and the economics and governance of autonomy.
What’s a runway-first approach (identity, APIs/events, data products, observability before scale), agentic AI with guardrails (planner–executor, human-in-the-loop, kill-switches), evidence-led governance (OKRs, SLOs, unit cost/CO₂), and disciplined decommissioning.
Who it’s Boards, CEOs, and CXOs seeking a clear path to measurable outcomes; CIO/CTO/CDAO/COO leaders designing platforms and operating models; transformation and product leaders running portfolios at scale.
Outcome if faster, safer decisions; lower unit cost; higher reliability and compliance; a culture that ships improvements every quarter—and a resilient, AI-powered enterprise that compounds value.
The narrative follows a lifecycle leaders can run Vision & Value → Portfolio & Governance → Target Architectures → Data/AI & MLOps → Build & Integrate → Pilot & Hypercare → Scale & Localize → Operate & Optimize. Each stage provides decision guides, reference patterns, checklists, and 30-60-90 day plans, allowing boards and executives to fund by outcomes, de-risk delivery, and prove benefits.
Vision & Value defines where to win now, framing a small set of measurable bets tied to customer moments, productivity, or risk reduction.
Portfolio & Governance replaces project thinking with persistent product teams, outcome-based funding, and a light but firm stage-gate.
Target Architectures set “clean-core ERP/CRM, smart edges” with API/event integration, zero-trust security, observability, and quality attributes.
Data Products, AI & MLOps turns data into governed products and establishes model pipelines, evaluation, and drift/safety controls.
Build & Integrate details the DevSecOps backbone, API engineering, event meshes, testing, and reversible release practices.
Pilot & Hypercare shows how to prove value with bounded scope, strict go/no-go criteria, and day-one telemetry.
Scale & Localize introduces release trains, localization packs, multi-region patterns, and decommissioning so value lands on the P&L.
Operate & Optimize aligns SRE, FinOps/GreenOps, and a Value Realization Office to run for reliability, cost, and benefits—not just uptime.
Platforms & Ecosystems offers pragmatic guidance across ERP/CRM, data/AI stacks, ServiceNow, and integration fabric.
A Strategy–Lifecycle–Software Matrix links strategies, phases, tools, and KPIs on one page for quarterly steering.
Industry Playbooks (manufacturing, BFSI, healthcare, public sector, etc.) provide first bets, metrics, and risks by sector.
The Human Enterprise covers change, skills, ethics, accessibility, and adoption—treating capability building as a product.
Future Horizon looks at agentic AI, multi-agent systems, digital twins, and the economics and governance of autonomy.
What’s a runway-first approach (identity, APIs/events, data products, observability before scale), agentic AI with guardrails (planner–executor, human-in-the-loop, kill-switches), evidence-led governance (OKRs, SLOs, unit cost/CO₂), and disciplined decommissioning.
Who it’s Boards, CEOs, and CXOs seeking a clear path to measurable outcomes; CIO/CTO/CDAO/COO leaders designing platforms and operating models; transformation and product leaders running portfolios at scale.
Outcome if faster, safer decisions; lower unit cost; higher reliability and compliance; a culture that ships improvements every quarter—and a resilient, AI-powered enterprise that compounds value.
332 pages, Kindle Edition
Published November 5, 2025
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