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Turning disruption data into recovery decisions

A single late inbound can cascade across passenger connections, crew duty limits and aircraft rotations. Airline operations teams must identify what matters most and act before constraints become irreversible.

A single late inbound can cascade across passenger connections, crew duty limits and aircraft rotations. Airline operations teams must identify what matters most and act before constraints become irreversible.

I designed an AI-assisted control centre for this high-pressure environment. It prioritises live disruption risks, makes downstream passenger and fleet dependencies visible, and helps controllers compare recovery actions before committing to a plan.

Scope

Concept work · Operational UX · AI-assisted workflows

Scope

Enterprise ⋅ AI Workflows

Scope

Enterprise · AI Workflows

Methods

Domain research · Legacy-tool analysis · Operational scenario mapping

Methods

Interviews ⋅ AI-assisted learning exploration

Outcome

A connected triage-to-recovery decision flow across passengers, fleet and crew

Role

Senior Product Designer

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