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 E — Vendor Market Guide
The 2026 CCaaS and CPaaS market map, a seven-vendor comparison, a hidden-cost checklist that catches the two-to-three-times multiplier on published pricing, and the reference-check questions worth asking.
Appendix D — Agentic AI Developer Toolkit (MCP)
A working map of the Model Context Protocol (MCP) — what it is, curated MCP servers by category for contact center use, three architectural composition patterns, and the checklist for building your own MCP server safely.
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.
Appendix A — Glossary
A single alphabetical A–Z glossary covering the contact center industry, AI, and compliance — every acronym you will hear in a CCaaS bake-off, a QBR, or a security review, defined in one sentence.
The Toolkit — Six Appendices
Six practical reference tools from The AI Contact Center Handbook — glossary, readiness checklists, compliance frameworks, MCP developer toolkit, vendor market guide, and CX math.
Chapter 12 — Strategic Vendor Selection and Implementation
The four vendor camps, the phased rollout playbook, contract terms that actually matter, the shift to outcome-based pricing, and a twelve-month calendar of what goes right and wrong.
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 10 — Guardian Agents and Trust by Design
The AI that watches the AI. Guardian Agents, voice biometrics, deepfake detection, and the multi-layer trust architecture behind AI-heavy contact centers in 2026.
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.
Chapter 7 — Hyper-Personalization and Omnichannel Journeys
Chapter 7 of the AI Contact Center Handbook — why omnichannel became multichannel, what optichannel replaces it with, live journey analytics, real-time speech-to-speech translation, and the trust line that separates helpful personalization from creepy surveillance.
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.
Part 3 — Quality & Measurement
Part 3 of the AI Contact Center Handbook — how quality assurance, workforce engagement, and personalization change when AI does the talking. Covers WEM (Ch 6) and hyper-personalization plus omnichannel journeys (Ch 7).
Chapter 6 — Intelligent Workforce Engagement Management (WEM)
Chapter 6 walkthrough from The AI Contact Center Handbook. WEM — the operational muscle behind scheduling, forecasting, and quality — is being rebuilt from Excel and Erlang C into a system that learns, monitors 100% of calls, and reforecasts intraday in ninety seconds.
Chapter 5 — The Experience Orchestration Platform (XOP)
Chapter 5 walkthrough from The AI Contact Center Handbook. The XOP is the sub-second decision layer above the CCaaS, CRM, and CDP — the brain that fuses live signals and CAMARA network APIs into a real-time answer.
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.
Part 2 — The Front Line
Part 2 of The AI Contact Center Handbook — what changes on the front line when agentic AI handles the routine work. Chapter 4 covers the human side of the shift; Chapter 5 covers the Experience Orchestration Platform that makes real-time decisions above every channel.
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.
Chapter 2 — The Architecture of Convergence: UCaaS, CCaaS, and CPaaS
A walkthrough of Chapter 2 of The AI Contact Center Handbook — the three acronyms behind every vendor pitch, why they are all converging into a single Communications Cloud, and what a buyer should actually evaluate.
Part 1 — The Landscape
Part 1 of The AI Contact Center Handbook. Three chapters that map the terrain before the tactics: the legacy trap, the new architecture, and the arrival of agentic AI.
Chapter 1 — The Cost of "How We've Always Done It"
A walkthrough of Chapter 1 of The AI Contact Center Handbook — why the legacy contact center is not a technology problem, but an operating-model tax paid every day in cash and in trust.
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.