AI Responsibility Capstone: Algorithmic Personalisation & Privacy Risk - Hotel Case Study

Course Type

Executive Leadership | AI Governance Capstone Simulation

Institution

C-Lab Institute

Overview

Artificial Intelligence in hospitality does not only personalise experiences — it reshapes guest privacy, trust, and brand integrity.

This capstone is the culminating stage of the C-Lab Institute AI Responsibility pathway. Participants are placed in a global hotel group that has deployed an AI-powered personalisation engine.

The system tracks guest preferences, spending patterns, sentiment data, and behavioural analytics to optimise pricing, room allocation, and targeted marketing.

Revenue is rising.
Customer engagement appears stronger.

However:

• Guests are unaware of the extent of behavioural profiling
• Regulators are reviewing cross-border data transfers
• A media investigation has raised concerns about “surveillance hospitality”
• A data leak has exposed sensitive guest patterns

The board must determine whether the AI system should continue, be redesigned, scaled globally, or suspended.

This is not a marketing decision.
It is a governance decision involving privacy, compliance, and brand trust.

Capstone Objective

Participants will act as Chair of the AI & Data Governance Committee and prepare a formal Board Advisory Memorandum recommending a responsible course of action.

The capstone evaluates the leader’s ability to:

• Identify privacy, data, and consumer protection risks
• Assess cross-border data transfer exposure
• Evaluate ethical limits of personalisation
• Design governance and oversight controls
• Propose transparency and consent frameworks
• Make a defensible deployment / restriction recommendation

What Participants Must Submit

A structured 1,800–2,000 word AI Governance Brief including:

Risk Identification

Data privacy risk
Regulatory exposure (GDPR / PDPA / global compliance)
Consumer transparency gaps
Algorithmic profiling risk
Cross-border data transfer implications
Cybersecurity vulnerabilities
Brand and reputational impact

Governance Framework Proposal

AI oversight committee structure
Clear data ownership & accountability
Consent and opt-out mechanisms
Data minimisation policies
Vendor & third-party accountability
Bias monitoring & fairness controls
Incident response and breach escalation protocol

Deployment Decision

Continue / Modify / Restrict / Pause

Conditions required for responsible personalisation

12-month governance and compliance roadmap

Reflection

“When does personalisation become intrusion — and how should responsible leaders draw that line?”

Assessment Criteria

Submissions are evaluated on:

• Depth of Privacy & Regulatory Analysis
• Governance Architecture Design
• Ethical Sensitivity to Consumer Trust
• Strategic Brand Risk Awareness
• Clarity and Defensibility of Recommendation

Award

🏅 300 Responsibility Coins
📜 C-Lab Institute AI Responsibility Capstone Certificate