AI · MVP
How to Get Started with AI – A Practical MVP Approach
Artificial intelligence does not require grand promises or multi-year projects. It needs a clear focus, data, and a willingness to learn.
1
Define a concrete problem that is costing you
Do not start with "what could AI do", but with "what is costing us too much right now".
Turnover in a key departmentUnpredictable weekend absencesLong onboarding for new employeesInconsistent quality or errors in processes
2
Collect basic data
It does not have to be perfect. AI can learn even from partial information. Typical sources:
Attendance and absencesShifts and schedulesRoles, departments, performance reviewsSurvey results, internal complaints or feedback
3
Choose one use case and time period
One clear focus beats ten generic ideas. E.g. "Flight Risk analysis for reception staff over the last 2 years".
4
Build a basic model and validate its accuracy
The AI model is trained on your data. Check whether it can identify who left and why.
5
Start using it – with alerts, not decisions
AI should alert HR or the manager: "This profile is similar to those who have left in the past." The decision stays with the people.
6
Measure results
Did you act in time? Did turnover decrease? Is onboarding faster? Are employees more engaged?