Before You Start

Week 0: Assessment

Identify the specific problem you're solving

Quantify the current cost (time, money, frustration)

Get leadership buy-in

Set success metrics (what does "working" look like?)

Week 1-2: Selection

Evaluate 2-3 potential solutions

Check integration requirements

Get pricing clarity (hidden costs?)

Request demos or trials

Week 3-4: Pilot Planning

Define pilot scope (start small)

Identify pilot participants

Set up integrations

Create success metrics

During Implementation

Week 5-6: Pilot Launch

Deploy to pilot group

Monitor usage and feedback

Track success metrics

Document issues

Week 7-8: Iteration

Address pilot feedback

Refine the solution

Train more users

Expand scope gradually

After Launch

Month 2-3: Scale

Roll out to full team/company

Establish ongoing training

Set up maintenance processes

Plan next AI initiative

Common Pitfalls

Starting too big — Pilot with one use case, one team

Ignoring change management — Technology is easy; adoption is hard

No success metrics — You can't improve what you don't measure

Skipping training — Users need to know how to use it

Quick Wins to Target First

Customer support automation

Document processing

Internal knowledge base

Meeting summaries

Data entry automation

Start with something that saves time immediately.

Your AI Implementation Checklist: 20 Questions Before You Start