The 90-day roadmap for deploying AI for Customer Service breaks the work into three phases — prepare, pilot, measure and scale — to help businesses get started the right way, avoiding costly failures. Zenify recorded a 35% reduction in processing time (approved).
TL;DR
- 90 days divided into 3 clear periods.
- First 30 days: data + goals.
- 30 days between: pilot 1 channel.
- Last 30 days: measure, refine, expand.
- Each stage has its own KPI to know progress.
Why do we need a roadmap?
Deploying AI isn't about flipping a switch — it needs the right order: data first, pilot second, scale last. The 90-day roadmap helps the team know what to do, when to do it, and what to measure (see Why AI projects fail).
Phase 1 — First 30 days: Preparation
Goal
Choose a clear, measurable problem.
Prepare data and knowledge.
Things to do
Choose 1 channel + 1 task most frequently (answer frequently asked questions).
Set KPIs first: process time, satisfaction, conversion.
Data readiness for the selected range (see Data readiness).
Build a knowledge base on a small scale (see Knowledge base for AI).
Choose tools just right (see 10 questions before buying AI).
Phase 2 — 30 days between: Pilot
Goal
Run AI on 1 channel, small volume.
Measure KPIs, detect errors early.
Things to do
Enable AI to answer frequently asked questions on 1 channel (see Pilot on 1 channel).
Sensitive sentence reviewer.
Collect wrong answers, refine weekly.
Measure KPI every week, compared to before.
Phase 3 — Last 30 days: Measure and expand
Goal
Evaluate effectiveness and decide on expansion.
Things to do
Clear summary of KPIs before/after.
Tính ROI sơ bộ (xem ROI của AI).
Expand to add more channels/jobs if effective.
Build governance before expanding (see AI governance).
Route tracking table
Phase | Key KPIs | Decision making
First 30 days | Clean data, sufficient KB | Pilot Ready
30 days between | Rate of correct and satisfied answers | Should
Last 30 days | ROI, before/after comparison | Expand or stop