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Case Study

AI Travel Agent Management

Prototyping human–AI collaboration for sustainable, efficient trip planning. Clarifying handoffs, trust signals, and escalation paths.

AI Ethics Interaction Workflow Design
AI travel interface

01Basic Info

Role
Product Designer, Systems Designer
Context / Team
Prototype sprint with operations partners and AI researchers
Tools
Figma, FigJam, Miro, Notion, GPT-5, Framer
Timeframe
Month & year
AI tools on screen Team collaborating on laptops

02Project Background

Placeholder — describe why a travel agent workflow needed AI support, and the existing friction in planning or servicing trips.

Placeholder — outline the goal: design collaboration patterns that keep humans in control while benefiting from automation.

Travel planning dashboard Workflow mapping

03Research & Direction

What we learned
  • Placeholder — research inputs (agent interviews, service audits, policy review).
  • Placeholder — insights about trust, transparency, and escalation.
  • Placeholder — operational constraints and compliance considerations.
What we decided
  • Placeholder — design principles for AI/human handoffs.
  • Placeholder — signals for confidence, data provenance, and overrides.
  • Placeholder — success measures around efficiency and guest satisfaction.
Interview notes Service blueprint wall

04Design & Rationale

  • Placeholder — decision about workflow stages and visibility.
  • Placeholder — pattern for recommendations with rationale and edits.
  • Placeholder — escalation pattern when AI is uncertain or out of policy.
Wireframes UI screens

05Results & Metrics

  • I was responsible for … (e.g., flows, prototyping, usability tests).
  • I worked closely with … (e.g., travel ops, AI safety, PM).
  • Since piloting, we saw … (time saved, fewer errors, clearer accountability).
Team reviewing results Dashboard metrics

06Bonuses

Placeholder — testimonials, lessons learned, or future roadmap.

Team celebration Roadmap notes
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