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Ai-Driven Hotel Reservations, Forecasting & Channel Optimiza
Published 2/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 2h 36m | Size: 3.67 GB [/center]
Apply AI to hotel reservations, demand forecasting, and channel optimization for smarter decisions
What you'll learn
Explain how AI is applied to hotel reservations, forecasting, pricing, and distribution.
Use AI-driven demand forecasts to support occupancy, ADR, and operational planning.
Apply AI-based pricing and revenue optimization strategies responsibly.
Analyze and optimize distribution channels using AI insights.
Understand system integration, governance, and future trends in AI-enabled hotel distribution.
Requirements
Basic understanding of hotel reservations, revenue, or distribution operations
No prior AI, data science, or programming experience required
Interest in revenue management, forecasting, or hotel commercial strategy
Access to a computer or mobile device with internet connection
Description
This course contains the use of artificial intelligence.This course provides a structured and practical introduction to how artificial intelligence is transforming hotel reservations, demand forecasting, pricing, and distribution strategies. Designed for hospitality professionals working in reservations, revenue management, and distribution roles, the course focuses on using AI to improve accuracy, responsiveness, and strategic decision-making-while maintaining human oversight and ethical responsibility.The course begins by establishing foundational knowledge of AI in hotel reservations, including the evolution of reservation systems and how AI analyzes guest booking behavior. Learners explore the data sources that power modern AI reservation systems and examine ethical and operational considerations related to automation, transparency, and control.The second module focuses on AI-powered demand forecasting. Learners gain an understanding of forecasting fundamentals and how machine learning models predict occupancy, ADR, and booking patterns. The module also covers real-time forecast adjustments, segmentation by channel and market, and how forecasts support both operational and commercial planning.The course then moves into AI-driven pricing and revenue optimization. Learners explore the relationship between reservations, forecasting, and pricing decisions, including dynamic pricing algorithms, length-of-stay controls, restriction management, and cross-channel price optimization. Emphasis is placed on the importance of human judgment and governance in AI-supported pricing decisions.A dedicated module on channel optimization examines how AI analyzes channel performance, supports direct booking strategies, manages OTA relationships, and automates monitoring of distribution strategies. The final module focuses on system integration and future trends, including connecting PMS, CRS, RMS, and channel managers, using AI dashboards for decision-making, developing AI skills for commercial teams, and creating a strategic roadmap for AI adoption in hotels.
Who this course is for
Hotel reservations managers and supervisors
Revenue managers and pricing analysts
Distribution and e-commerce managers
Hotel commercial leaders and operations managers
Hospitality students preparing for revenue or reservations roles
