In AI + cloud businesses, “Customer Success” can’t be a team that cleans up problems after the sale. It must be an operating system: a cross-functional way of working that makes customer outcomes and renewals: predictable.

This book shows you how to build that system end-to-end. You’ll learn how to run Customer Success as a measurable cadence focused on outcomes (not activity), how to design onboarding around Time-to-First-Value and Time-to-Target-Value, and how to make integrations, implementation, and change management repeatable instead of heroic.

Then the AI reality hits: value becomes probabilistic, expectations must be engineered, and trust becomes a deliverable. You’ll get practical guidance for AI readiness discovery, evaluation in the customer’s language, managing hallucinations without losing credibility, monitoring drift, and handling incidents with a “trust response plan.” Along the way, you’ll operationalize responsible AI governance, transparency, auditability, privacy, and fairness without turning CS into a compliance theater.

Finally, the book scales: segmentation, coverage models, health scores that predict outcomes, lifecycle programs, QBRs that actually renew, and a renewal/expansion framework that turns evidence into executive conviction.

Whether you’re a CSM, CS leader, founder, or cross-functional partner in Product, Sales, or Delivery, this handbook is your blueprint to build Customer Success that works in the AI era reliably, defensibly, and at scale.

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