AI implementation strategyPublished: 2026-10-10Last Reviewed: 2026-10-15
Your first AI project: a practical checklist
A 10-point executive and operational checklist covering workflow definition, data boundaries, human ownership, pilot testing, and post-launch measurement.
TECHNICAL REVIEW: Advisory Practice Lead
KEY POINTS FOR BUSINESS LEADERS
- Define the operational problem in one sentence without mentioning AI.
- Confirm where the input data lives and whether it is accurate and accessible.
- Decide who reviews the output and what happens when the system is uncertain.
- Run a bounded pilot with real edge cases before expanding across the organization.
What must be decided before building an AI workflow?
Use these five questions during your Discover and Design phases:
1. What is the exact trigger and desired output? (e.g., 'When an inquiry arrives, prepare a scored CRM record and draft response.')
2. Which specific documents or tables is the system allowed to read?
3. What actions are strictly prohibited without human click-to-approve sign-off?
4. Which person on your team owns the workflow once it goes live?
5. How is this work handled today, and how will we evaluate whether the pilot is cleaner and more reliable?
How should you test and launch the pilot?
Never launch an AI workflow straight to 100% of customer traffic without a shadow or draft phase:
- Test with historical real-world inputs—including messy, incomplete, and unusual requests.
- Verify that fallback and escalation notifications reach the right person when the system abstains.
- Train the staff members who operate the human checkpoint so they know what to verify.
- Schedule a 30-day post-launch review to inspect override logs and refine rules.
Practical operational examples
- Shadow-Mode Pilot: Running an intake classification agent alongside human coordinators for two weeks to verify accuracy before turning on live routing.
Explicit Boundaries & Limitations
A checklist ensures disciplined scoping, but regulated industries (such as healthcare, legal, or financial services) must also include formal legal and compliance review of data handling agreements.
Frequently Asked Questions
How do we know if our organization is ready to run this checklist?
Take our 3-minute AI Readiness Assessment to score your foundation across strategy, workflow clarity, data, software integrations, ownership, and governance.
PRIMARY SOURCES & REFERENCES
RELATED GLOSSARY DEFINITIONS
RELATED WORKFLOW: Inquiry qualificationView in Use-Case Library →
Turn this guidance into a practical workflow
Use the AI Opportunity Finder or talk directly with our Atlanta implementation team.