What a Sensible First Step Looks Like?
Once a business decides that AI might be helpful, the temptation is to move quickly.
But a sensible first step with AI isn't about speed. It's about confidence.
The right first step is small, focused, and low-risk β something that proves value without disrupting how the business runs.
Start Where Friction Is Felt Most
The best place to begin is usually where frustration already exists.
Look for areas where: people repeat the same work daily, questions come up again and again, errors require rework, and tasks are necessary but draining.
When AI improves one of these areas, the benefit is immediately visible.
Keep the Scope Narrow
A strong first use case should: focus on a single process, involve a small group of users, have a clear goal, and be easy to explain.
Narrow scope reduces risk and makes success easier to recognize.
Trying to solve too much at once often creates confusion instead of value.
Define Success in Simple Terms
Before introducing AI, it helps to agree on what success looks like β without complex metrics.
Success might mean: fewer interruptions, faster turnaround, fewer mistakes, clearer information, or less stress.
If people feel the improvement, the initiative is working.
Involve the People Affected
AI should never be introduced to people β it should be introduced with them.
Involving employees early: builds trust, surfaces real concerns, improves adoption, and reveals edge cases.
People are far more open to AI when they feel respected and supported.
Observe Before Expanding
After AI is introduced, resist the urge to immediately expand its use.
Instead: observe how it's used, listen to feedback, make small adjustments, and confirm it's actually helping.
This period of observation is where real learning happens.
Confidence Comes from Experience
After one successful use case, something important shifts.
AI becomes: familiar instead of intimidating, practical instead of abstract, and trusted instead of questioned.