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The professor gave Quindaria just this:

Course: Technology, Innovation & Society
Level: Final-year undergraduate
Primary topic: Artificial intelligence
Secondary topic: Ethical, social & environmental implications
Selected learning outcomes:
  • LO1 — Explain how emerging technologies such as AI are reshaping organisations and the way they work.
  • LO2 — Weigh the economic, ethical, social and environmental trade-offs of adopting an emerging technology.
  • LO3 — Use real-world cases and evidence to judge the opportunities and risks of a technology decision.

↓ In minutes, Quindaria built:

QuindariaReady-to-use activity

Case study with a strategic decision · ~90 min

Deploying an AI Guest-Service Assistant: The Meridian Hotels Decision

Context

Meridian Hotels, a mid-scale European group of 40 properties, has spent six months piloting an AI guest-service assistant — a chat-and-voice system that handles bookings, requests, upsells and concierge questions 24/7 in 12 languages. The pilot results are in, and the board wants a recommendation at next week's strategy review: scale it group-wide, keep it limited, or stop it. You are advising the Chief Operating Officer. You have the pilot data below.

The pilot data

Cost per handled request−38% vs. human front desk
Guest satisfaction — under-35 guests+11 points
Guest satisfaction — over-55 guests−9 points (“I wanted a person”)
Front-desk hours affected~30% of routine tasks automatable
Data & privacyStores conversation + booking history; consent flow still manual
Energy footprintCloud inference adds ~6% to digital energy use

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