AI Readiness Checklist
Nine-question AI Readiness Checklist turns chaos into clarity. Score yourself, land in a tier, and follow the narrative playbook that took one firm from 14 → 29 points in 60 days while halving support hours. Grab the 10-min survey for a personalized roadmap.
AI Readiness Checklist
The 10-minute pit stop that keeps your first pilot from exploding at turn one.
Prologue – The Morning the Server Room Got Louder
Tuesday, 8:12 a.m.
The CFO barges into the Level 10® clutching a printout titled “AI WILL SAVE US $4 M.”
The Visionary lights up like it’s Christmas and IPO day rolled together.
Ops crosses their arms—half the critical data lives in 17 spreadsheets and one disgruntled analyst’s head.
You, the Integrator, silently count the ways this could burst into flame before lunch.
That’s the moment I hand the team a nine-question scorecard, set a timer for ten minutes, and watch clarity replace chaos.
That one-pager became the AI Readiness Checklist you’re reading today.
1 — Why This Checklist Exists
AI pilots rarely die because the algorithm misbehaved; they die from people, process, and politics. A 99.9 % accurate model can still crash if Legal panics, the dataset is dirty, or no one knows who owns the prompt library.
The checklist is a flashlight: point it at six EOS® Components plus budget and change management. Where it shines red, you fix first. Where it shines green, you press the throttle.
2 — The Nine-Question Checklist
- VISION: Can every leader explain—in one sentence—why AI matters to the business this quarter?
- PEOPLE / CHART: Is there one named seat with 10 hours/week carved out to own the pilot?
- DATA: Is the core dataset centralized, clean, and permissioned—no heroic copy-pasting required?
- ISSUES: Have top 3 fears (job loss, bias, security) been surfaced and IDS’d?
- PROCESS: Does an existing SOP describe 80 % of the workflow the model will enter?
- TRACTION / SCORECARD: Which leading KPI will prove value in ≤ 30 days?
- BUDGET: Is the tooling spend (< $2 K) pre-approved, sandbox hours booked?
- CHANGE MANAGEMENT: Does a comms plan exist so frontline staff aren’t blindsided on Monday?
- ITERATE OR KILL: Is a day-90 decision gate—scale, pivot, or stop—written into the Rock?
Scoring
| Tier | Score | What the next 90 days look like |
|---|---|---|
| EMERGING | 0-15 | Data & culture bootcamp, no code yet. |
| DEVELOPING | 16-30 | One tightly-scoped pilot with a single KPI. |
| READY | 31-45 | Full 90-day AI Rock, weekly KPIs, budget to scale wins. |
Why three tiers? Because “sorta ready” isn’t a strategy.
3 — Story Lap 1: From 14 to 29 in Sixty Days
“I swore we were ‘Ready.’ The checklist slapped us with a 14. Sixty days later we hit 29—and our chatbot cut support hours in half.”
— Lena Ortiz, CEO, ApexParts
| Metric | Day 0 | Day 60 | Δ |
|---|---|---|---|
| Checklist Score | 14 | 29 | +15 |
| Manual support hours / week | 46 | 23 | –50 % |
| NPS | 38 | 52 | +14 |
Three Tuesday Sprints
- Data Detox—seven orphan spreadsheets merged; two deleted.
- Fear Slam—45-minute honesty session; “robots steal jobs” became a training budget line-item.
- Sandbox Hour Bank—10 protected hours/week for the pilot owner; no more “after hours hacking.”
Result: a working chatbot + a calmer team + an Integrator who finally got invited to lunch.
4 — Where You Go from Here (Three Garage Stops)
A. Emerging Garage (0-15 pts) → Plug the Tire Leak
- This Week: Appoint a “data janitor” with the authority to delete duplicates.
- Friday: Add KPI Manual Hours Saved—track minutes copy-pasted into reports.
- Mindset: You’re patching leaks, not painting flames on the hood.
B. Developing Garage (16-30 pts) → Test-Track One Corner
- Pilot Rule: One lever only—Generative or RPA, never both.
- Lightning Rock: 4-week timeline, <$2 K tools, single throat to choke.
- Scorecard: Leading KPI turns red if owner spends <4 hrs/week in the pilot.
C. Ready Garage (31-45 pts) → Race Day
- Rock Title: Fits on one line; comma means two Rocks.
- IDS™ Discipline: AI issue sits top of the list until green.
- Audit on Day 70: Fractional CAIO reviews model drift; no late surprises.
5 — Story Lap 2: CFO Eats Their Words
Remember the CFO from the opening? Three months after scoring a mediocre 22, she reported:
| Metric | Before | After 90 d | Δ |
|---|---|---|---|
| Cash-Flow Forecast | 11 days | 34 days | +23 |
| Forecast Accuracy | ± 19 % | ± 6 % | Better |
| CFO Slack messages at 10 p.m. | Nightly | Zero | Team rejoices |
Her quote to the board: “Turns out readiness isn’t a ‘nice-to-have’; it’s the entire brake system.”
6 — Two KPIs You Should Track Starting Monday
| KPI | Why It Matters | 5-Min Setup |
|---|---|---|
| Manual Hours Saved | Converts skeptics faster than a deck. | Pilot owner logs minutes cut/day in a shared sheet. |
| Model Assist % | Shows if staff trust AI. | Track accept vs overwrite events in logs. |
7 — Frequently Mumbled Objections
“Can’t we just say we’re Ready?”
Sure—if you enjoy 3 a.m. outages and apology emails.
“We scored a 30. Round up?”
Treat yourselves as Developing for one quarter, retest, then hit the gas.
“Do we need a CAIO?”
You need one neck on the line for model risk. Two hours/week from the right fractional expert beats six engineers pointing fingers.
8 — Your Personalized Roadmap in 24 Hours
Get a tier-specific action plan before tomorrow’s stand-up.
📊 Take the AI Readiness Assessment + Get Complete Toolkit
The 9-question checklist that took one firm from 14 → 29 points:
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AI Speed | EOS® Discipline
See you on the track. 🏁
© 2025 WorldWide AI Consulting LLC + Traction.AI • Built on Ghost
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