Where could AI assist existing work?
We scoped internal automation and tool-supported work inside each team instead of starting with a generic list of AI features.
How do you give teams useful ways to work with AI without removing judgment or control?
The airline wanted its Commercial and Marketing teams to use AI inside work they already owned. We turned that broad goal into separate instruction, applied practice, and a repeatable weekly reference for each team.
We scoped internal automation and tool-supported work inside each team instead of starting with a generic list of AI features.
Commercial and Marketing received separate material built around their own responsibilities.
Each team received a weekly workflow guide that carried the method into recurring work.
The engagement moved from team context to separate instruction, hands-on application, and a weekly reference. People kept responsibility for reviewing the work and making the final decision.
Map recurring work and identify where tools or internal automation could assist.
Build a master class and facilitator material for each business team.
Use hands-on exercises to apply the method to work the teams already owned.
Turn the instruction into a team-specific workflow guide for recurring work.
What we supplied: separate decks, facilitator material, hands-on exercises, and weekly workflow guides.
What stayed human: employees reviewed the work and remained responsible for every final decision.
The working method stayed consistent. The examples, exercises, and weekly guide changed with the team.
The team received its own master-class material, applied exercises, and weekly workflow guide.
The same method was rebuilt around the Marketing team rather than reused as a generic presentation.
Commercial and Marketing each received a tailored master class, facilitator material, hands-on exercises, and a weekly workflow guide. Employees reviewed the work and retained responsibility for every final decision.
Separate material, applied practice, and a weekly guide gave each team a practical way to work with AI while keeping review and judgment human.