The AI Contact Center Handbook
A practical field guide to customer experience in the age of agentic AI — chapter by chapter, for teams evaluating AB Support.
Appendix F — CX Math and Operational Models
The four pieces of math a CX leader should be able to sketch on a whiteboard — Erlang C with a worked example, Erlang O concurrency, LLM inference economics with model routing and caching, containment arithmetic, and blended cost per contact.
Appendix B — Readiness Checklists
Diagnostic tools for the voice AI transformation: a 20-question readiness assessment, a 25-question vendor security screen, a DPIA template, five survey designs, an executive readiness agenda, and the weekly operating rhythm for a live AI program.
Chapter 9 — Keeping AI out of PCI Scope
Why post-call redaction fails PCI DSS v4.0 audits, how the LLM Scope Rule silently pulls modern contact-center systems into scope, and the pause-and-resume architecture with network-level DTMF masking the industry has converged on.
Chapter 11 — The Changing Job Market and New Enterprise Roles
Which contact center jobs shrink, which grow, and how today's agents actually bridge into the new roles. The workforce transition as a role-definition problem, not a headcount problem.
Chapter 8 — Navigating the Regulatory Minefield
A working map of the five regulations every AI-powered contact center leader needs to know cold — GDPR, CCPA, HIPAA, TCPA, and the EU AI Act — plus the governance-by-design apparatus that keeps modern operations defensible.
Part 5 — Execution
Part 5 of The AI Contact Center Handbook — where the book stops describing the terrain and starts telling you what to do: trust architecture, the changing workforce, and vendor selection.
Part 4 — Governance & Safety
An overview of Part 4 of the AI Contact Center Handbook — the governance, compliance, and safety layer that keeps AI-mediated customer interactions inside the law and inside the trust boundary.
Chapter 4 — The New Role of the Human Agent
Chapter 4 walkthrough from The AI Contact Center Handbook. Agentic AI takes the routine 80% of interactions; the human agent's job becomes higher-stakes, higher-EQ, higher-paid — and needs to be rebuilt from the ground up.
Chapter 3 — The Rise of Agentic AI
A walkthrough of Chapter 3 of The AI Contact Center Handbook — what "agentic" actually means, why a chatbot is not an agent, the three ingredients (model + tools + memory), and the seven design principles that separate production systems from failed pilots.
The AI Contact Center Handbook — A Field Guide to Customer Experience in the Age of Agentic AI
A preview of Sho Shimoda's new book — what agentic AI actually means, why it changes the operating model of customer experience, and what it looks like in production inside Microsoft Teams.