Mistake 1: No Clear Problem
Don't implement AI for AI's sake. Start with a specific problem.
Fix: Write one sentence: "AI will help us [do what] by [how]."
Mistake 2: Trying to Do Everything
Starting too big is the #1 killer of AI projects.
Fix: Start small. One use case. One team. Expand after proving ROI.
Mistake 3: Ignoring Data Quality
AI is only as good as your data. Garbage in, garbage out.
Fix: Clean data first. AI can't fix bad inputs.
Mistake 4: No Human Oversight
AI makes mistakes. Without checkpoints, those mistakes compound.
Fix: Build in human review for high-stakes decisions.
Mistake 5: Ignoring Change Management
Technology is easy. Getting people to use it is hard.
Fix: Involve end users early. Train them. Listen to feedback.
The Common Thread
All five mistakes share one root cause: rushing to technology before understanding the problem.
Start with the problem. The technology follows.