AI Applications in Hospitality and Hotel Personalization Training Course

Module 1: Foundations of AI in the Hospitality Industry

• Evolution of hospitality tech: From legacy PMS to Cognitive Hotels
• Identifying high-impact AI use cases across the guest lifecycle
• Overview of the AI stack: Machine Learning, Deep Learning, and NLP in a hotel context
• Understanding the role of Big Data and guest profile consolidation
• Challenges of AI adoption: Overcoming technical debt and staff resistance
• Practical session: Conducting a digital maturity audit for a sample hotel property

Module 2: AI-Driven Revenue Management and Dynamic Pricing

• Beyond traditional rules: Implementing ML-based pricing engines
• Real-time demand forecasting: Integrating local events, weather, and flights
• Competitive set analysis: Using AI to monitor market shifts instantly
• Channel management optimization: Predicting the most profitable booking paths
• Automated rate distribution across OTAs and direct channels
• Practical session: Using a predictive model to adjust room rates based on a simulated market spike

Module 3: Hyper-Personalization and the Modern Guest Journey

• Building a "Unified Guest Profile" using data from multiple touchpoints
• Recommendation engines: Tailoring room types, amenities, and add-ons
• Behavioral triggers: Anticipating guest needs before they are articulated
• Personalizing the pre-arrival and in-stay digital communication
• Upselling and cross-selling through intelligent, non-intrusive AI prompts
• Practical session: Designing a personalized guest itinerary using behavioral data markers

Module 4: NLP and AI Chatbots for Guest Support

• Implementing 24/7 automated concierge services across WhatsApp, Web, and In-room
• Intent recognition: Handling room service, housekeeping, and local info requests
• Multi-lingual support: Breaking language barriers with instant AI translation
• Seamless human handoff: When and how to transition to a live agent
• Voice AI: Managing guest requests through smart speakers in guest rooms
• Practical session: Building a basic chatbot flow for handling late check-out requests

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Module 5: Predictive Analytics for Occupancy and Staffing

• Forecasting seasonal and event-based occupancy with high precision
• Labor optimization: Aligning housekeeping and front-desk schedules with predicted load
• Reducing "No-Shows": Using predictive models to identify high-risk bookings
• Energy management: Predicting occupancy to optimize HVAC and lighting costs
• Supply chain and inventory forecasting for hotel amenities
• Practical session: Developing a staffing schedule based on a 7-day occupancy forecast model

Module 6: Computer Vision and IoT for Smart Hotel Operations

• Frictionless check-in: Facial recognition and digital key integration
• Smart Room automation: IoT sensors for personalized temperature and lighting
• Computer vision for safety: Identifying security anomalies in public areas
• Automated maintenance: Using sensors to predict equipment failure (e.g., elevators, chillers)
• Queue management: Using AI to monitor and reduce front-desk wait times
• Practical session: Mapping an IoT sensor network for a "Smart Suite" concept

Module 7: AI in Food and Beverage (F&B) Optimization

• Intelligent menu engineering: Predicting popular dishes and optimizing pricing
• Waste reduction: Using AI to forecast food prep requirements and inventory
• Personalized dining recommendations based on guest dietary preferences
• Automated table management and reservation forecasting
• AI in the kitchen: Robotics and automated cooking consistency
• Practical session: Analyzing F&B sales data to optimize a seasonal menu using AI insights

Module 8: Sentiment Analysis and Reputation Management

• Mining "Voice of the Guest" data from TripAdvisor, Google, and social media
• Automated sentiment tagging: Identifying specific friction points (e.g., "slow WiFi")
• Real-time alert systems for negative guest feedback during a stay
• AI-assisted review responses: Maintaining brand voice while addressing concerns
• Benchmarking reputation against competitors using automated NLP tools
• Practical session: Performing sentiment analysis on a batch of 100 guest reviews to identify top 3 service gaps

Module 9: Hyper-Targeted Marketing and Loyalty AI

• Predicting guest churn: Identifying loyalty members at risk of leaving
• Personalized email marketing: Optimizing send times and content for higher conversion
• Attribution modeling: Understanding which AI-driven campaigns drive direct bookings
• Dynamic website personalization: Changing landing pages based on visitor intent
• Loyalty program optimization: Tailoring rewards to individual guest preferences
• Practical session: Creating a targeted re-engagement campaign for "at-risk" past guests

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Module 10: AI Ethics, Privacy, and Human-AI Synergy

• Navigating GDPR and data protection laws in the age of guest profiling
• Addressing algorithmic bias: Ensuring fair treatment across guest demographics
• The "Human Touch" vs. Automation: Balancing efficiency with authentic hospitality
• Transparency: Communicating AI usage to guests in a trustworthy manner
• Developing a long-term AI roadmap for a hospitality organization
• Practical session: Drafting a "Guest Data Privacy Manifesto" for an AI-integrated hotel

Requirements:

Participants should be reasonably proficient in English.

Applicants must live up to Armstrong Global Institute admission criteria.

Terms and Conditions

1. Discounts: Organizations sponsoring Four Participants will have the 5th attend Free

2. What is catered for by the Course Fees: Fees cater for all requirements for the training – Learning materials, Lunches, Teas, Snacks and Certification. All participants will additionally cater for their travel and accommodation expenses, visa application, insurance, and other personal expenses.

3. Certificate Awarded: Participants are awarded Certificates of Participation at the end of the training.

4. The program content shown here is for guidance purposes only. Our continuous course improvement process may lead to changes in topics and course structure.

5. Approval of Course: Our Programs are NITA Approved. Participating organizations can therefore claim reimbursement on fees paid in accordance with NITA Rules.

Booking for Training

Simply send an email to the Training Officer on training@armstrongglobalinstitute.com and we will send you a registration form. We advise you to book early to avoid missing a seat to this training.

Or call us on +254720272325 / +254725012095 / +254724452588

Payment Options

We provide 3 payment options, choose one for your convenience, and kindly make payments at least 5 days before the Training start date to reserve your seat:

1. Groups of 5 People and Above – Cheque Payments to: Armstrong Global Training & Development Center Limited should be paid in advance, 5 days to the training.

2. Invoice: We can send a bill directly to you or your company.

3. Deposit directly into Bank Account (Account details provided upon request)

Cancellation Policy

1. Payment for all courses includes a registration fee, which is non-refundable, and equals 15% of the total sum of the course fee.

2. Participants may cancel attendance 14 days or more prior to the training commencement date.

3. No refunds will be made 14 days or less before the training commencement date. However, participants who are unable to attend may opt to attend a similar training course at a later date or send a substitute participant provided the participation criteria have been met.

Tailor Made Courses

This training course can also be customized for your institution upon request for a minimum of 5 participants. You can have it conducted at our Training Centre or at a convenient location. For further inquiries, please contact us on Tel: +254720272325 / +254725012095 / +254724452588 or Email training@armstrongglobalinstitute.com

Accommodation and Airport Transfer

Accommodation and Airport Transfer is arranged upon request and at extra cost. For reservations contact the Training Officer on Email: training@armstrongglobalinstitute.com or on Tel: +254720272325 / +254725012095 / +254724452588