If you can answer "yes" to all 24 of these, your AI project ships clean. If you can't answer "yes" to half of the "Before you start" items, you're not ready, regardless of how good the vendor's deck looks. Print this list, take it to any vendor pitch, and ask which 24 items they help with directly. The answer tells you whether you're hiring an implementation partner or a tool reseller.
TL;DR.
The 24 items break into three phases: 8 readiness items before any vendor selection, 8 build-quality items during construction, 8 operational items after launch. Failing several items in any one phase is a strong signal of project risk. The 3 most-skipped items: #6 (CRM data quality), #16 (written rollback plan), #20 (false-confidence logging). Use this list to evaluate vendors, score your own readiness, and run weekly health checks during the first 90 days. The checklist is free, no email gate, no PDF wall.
How to use this checklist.
- Before any vendor selection: score yourself on items 1-8. If you can't check at least half, slow down. The vendor problems you're trying to solve usually aren't actually vendor problems; they're readiness problems.
- During vendor evaluation: ask any candidate vendor to walk through items 9-16. Which do they handle, which do they expect you to do, which do they not address? The gaps tell you whether you're hiring an implementation partner or a tool reseller.
- During build: review items 9-16 at week 1 + week 4. Anything not yet addressed by week 4 needs an explicit conversation about why.
- After launch: use items 17-24 as your weekly health check for the first 90 days. Anything red for 2 consecutive weeks = escalation conversation.
- At day 90: use item 24 (the expand/kill/hold decision) as a forcing function. No more open-ended pilots.
Before you start (8 items).
- I have named ONE bottleneck I am solving, in one sentence.
- I can quantify the bottleneck (hours per week, dollars per month, or a percentage).
- I have written the success metric and the threshold for "this worked."
- I have committed weekly internal time for the build period.
- I know which CRM holds the customer data this project will touch.
- I have confirmed my CRM data is clean enough to use (or budgeted to clean it).
- I have approved a budget range that matches a realistic project size.
- I have one decision-maker on my side empowered to approve in week 1.
Deep notes on the "Before you start" items.
- On #1 (one bottleneck): If you can list 5 bottlenecks, you don't have a project yet, you have a wish list. Pick one. The other 4 wait.
- On #3 (success metric): "We want to use AI more" is not a metric. "We want every new lead answered within a set time we can measure" is a metric. The difference is whether the result is measurable.
- On #4 (weekly internal time): If the owner can't commit this, the project will fail. AI implementation is not a magic outsourcing where you sign a check and walk away. The owner has to be in the room (or on Slack) throughout the build.
- On #6 (CRM data quality): Often the most underestimated cost in the whole sequence. Dirty data = confident garbage out. Budget time for cleanup before the AI deployment makes sense.
- On #8 (decision-maker): Multi-stakeholder approval cycles kill AI projects faster than any technical problem. One person who can decide in week 1.
During build (8 items).
- The vendor has written a one-page spec, not a deck.
- The spec includes acceptance criteria at 30, 60, and 90 days.
- The project has a go-live date, not just a "pilot" milestone.
- Integrations are listed by name (CRM, phone, calendar, etc.), not vaguely.
- I know exactly which conversations the AI will handle and which it will escalate.
- My team has been informed and assigned roles for handoffs.
- Shadow-mode testing is planned before live cutover.
- I have a written rollback plan if the launch fails.
Deep notes on the "During build" items.
- On #9 (one-page spec): If the vendor's documentation is a long slide deck, you're paying for slides. Implementation specs are tight: scope, integrations, acceptance criteria, go-live date, rollback. One page.
- On #11 (go-live date): The single most-skipped commit in vendor proposals. Without a go-live date, "pilots" run forever. Pin the date in writing.
- On #15 (shadow-mode testing): Run the AI in parallel with the existing process before cutover. Watch where it agrees with the human, where it disagrees, why. Tune from there.
- On #16 (rollback plan): Many teams skip this assuming launches will work. The teams that ship clean have it written, even if they never use it. The act of writing it surfaces edge cases the vendor missed.
After launch (8 items).
- I have a weekly review meeting on the calendar for the first 90 days.
- The metric defined in step 3 is being tracked and visible.
- Escalated conversations are reviewed weekly and used to tune.
- False-confidence cases (AI was wrong but acted certain) are logged separately.
- Customer feedback channels are monitored for any AI-related complaints.
- Internal SOPs are written and accessible to anyone on my team.
- There is a documented owner for ongoing maintenance.
- At day 90, I have a clear decision: expand, kill, or hold.
Deep notes on the "After launch" items.
- On #17 (weekly review): Keep it short. Same time every week. Owner + vendor + one team member who works with the AI daily. Three questions: what worked, what didn't, what changes this week.
- On #20 (false-confidence logging): Often-skipped operational item. AI getting things wrong while sounding confident is the highest-impact failure mode. Log every one, review weekly, tune the knowledge base or escalation rules to prevent recurrence.
- On #21 (customer feedback channels): Email, GBP reviews, social DMs, support tickets. Set up an alert for any mention of the AI by name or by description ("the robot," "your bot"). Address proactively.
- On #24 (day-90 decision): The forcing function. Without it, half-working systems linger and erode budget + team trust.
The 3 most-skipped items (and why they matter).
| Item | Why teams skip it | What it costs to skip |
|---|---|---|
| #6 CRM data quality | Looks like "boring" prep work; nobody wants to do dedupe | AI produces confident garbage on bad data; trust evaporates quickly |
| #16 Written rollback plan | Assume launches will work; "we'll figure it out" | Bad launches that lack a rollback plan take far longer to recover from and erode team confidence |
| #20 False-confidence logging | Sounds tedious; "we'll just fix things as they come up" | Repeat errors compound; customers notice; trust in AI never recovers |
Tools that help with the checklist.
- For Step 3 (success metric): a shared Google Sheet or Notion doc that lives on the project channel
- For Step 6 (data cleanup): OpenRefine (free), Dedupely, or your CRM's native dedupe tool
- For Step 11 (go-live date): a calendar invite that includes vendor + owner + team lead. Public commitment.
- For Step 15 (shadow-mode testing): CRM tagging on AI-touched vs human-touched conversations to enable comparison
- For Step 16 (rollback plan): a documented one-page "if this breaks, here's what we do" with on-call contacts
- For Step 19 (escalation review): tag escalations in the CRM with a custom field; review in the weekly review meeting
- For Step 20 (false-confidence logging): a Slack channel or Notion table where the team drops examples as they happen
- For Step 22 (SOPs): Loom + a shared Notion or Google Doc with role-by-role responsibilities
Vendor questions, framed against the checklist.
- "Will you give me a one-page spec with go-live date and acceptance criteria? (Item 9-11)"
- "Which of these integrations will you handle, and which do you expect me to handle? (Item 12)"
- "Walk me through exactly which conversations the AI will handle vs escalate. (Item 13)"
- "What does shadow-mode testing look like in your engagement? (Item 15)"
- "What's the rollback plan if launch fails? (Item 16)"
- "Who owns the system after launch? Do I get admin access? (Item 23)"
- "What does the day-90 decision meeting look like? Who attends? (Item 24)"
FAQ.
How do I use the AI implementation checklist?
Print it. Bring it to any vendor pitch. Ask the vendor which of the 24 items they help with directly, which they expect you to do yourself, and which they don't address. The answer tells you whether you're hiring an implementation partner or a tool reseller. Use it again at 30, 60, and 90 days to score project health.
How many items must I check before starting?
All 8 'Before you start' items. If you can't check half of them, you're not ready. Spending the first month doing this work saves you months of unwinding a project that never had clear acceptance criteria.
What's the most-skipped checklist item?
Item 16 (written rollback plan). Many teams assume launches will work and have no documented response when they don't. The teams that ship clean have the rollback plan written before go-live, even if they never use it.
Can I use this checklist for non-AI projects too?
Yes. Steps 1-8 (bottleneck definition, success metric, budget, decision-maker) and 17-24 (post-launch measurement and ownership) apply to any operational project. Items 9-16 are AI-specific (vendor spec, shadow-mode testing, escalation paths).
Is this checklist free?
Yes. No email required, no PDF download wall, no gated newsletter signup. Read it on this page. Copy it into your own doc. Use it however you want.
What if a vendor refuses to commit to the checklist items?
That tells you what you need to know about the vendor. Walk. Real implementation partners will work through every item, push back where their approach differs, and document the gaps. Vendors who refuse are selling decks.