Why Attend
Artificial intelligence is creating new opportunities across the real estate lifecycle, from development feasibility and investment analysis to building operations, maintenance, energy management, tenant experience, and portfolio decision-making. The challenge for real estate and facilities professionals is determining where AI can deliver measurable value and how it can be integrated with existing property data, building systems, and management processes.
This Artificial Intelligence (AI) in Real Estate Development and Facilities course provides a practical business and operational perspective on applying AI, machine learning, generative AI, predictive analytics, computer vision, digital twins, and intelligent building technologies. Participants explore how AI can support site and development analysis, property portfolio management, predictive maintenance, space utilization, energy optimization, facilities management, and tenant services while addressing data quality, privacy, cybersecurity, governance, and implementation risks.
Professional Problems This Course Is Designed to Solve
Fragmented property and facilities data: Connecting information from building systems, IoT sensors, maintenance records, occupancy data, financial systems, and property platforms to support better decisions.
Reactive facilities maintenance: Moving from breakdown-driven maintenance toward predictive and condition-based maintenance using asset data and AI-supported analytics.
Rising building operating costs: Using data and AI to identify opportunities for energy optimization, resource efficiency, maintenance improvement, and operational cost reduction.
Poor space utilization: Applying occupancy analytics and intelligent workplace data to improve space planning, utilization, and portfolio decisions.
Complex real estate development decisions: Supporting feasibility analysis, demand assessment, scenario modelling, and development planning with AI-assisted analysis.
Inconsistent tenant and occupant experience: Using AI-enabled service management, automation, and intelligent building capabilities to improve responsiveness and building experience.
AI implementation and governance risks: Managing data quality, privacy, cybersecurity, algorithmic limitations, vendor dependency, and human accountability in AI-enabled property environments.
Course Methodology
The programme combines instructor-led sessions, demonstrations, real estate and facilities case studies, AI-assisted analysis exercises, building operations scenarios, group workshops, and implementation planning. Participants examine practical applications across the property lifecycle and develop an AI use-case portfolio based on business value, data requirements, operational feasibility, risk, and measurable outcomes.
Course Objectives
By the end of this course, participants will be able to:
Understand the role of AI across real estate development, property management, and facilities management
Identify high-value AI applications across the real estate and building lifecycle
Apply AI-assisted analysis to development feasibility and property decision-making
Understand predictive maintenance and intelligent asset management applications
Use occupancy and space data to support workplace and portfolio optimization
Evaluate AI opportunities for building energy and operational efficiency
Understand the role of IoT, building management systems, digital twins, and computer vision in intelligent facilities
Apply generative AI to facilities, property, and management workflows
Evaluate data, privacy, cybersecurity, governance, and implementation risks
Develop an actionable AI roadmap for real estate and facilities operations
Target Audience
This course is suitable for:
Real estate development managers
Property and asset managers
Facilities managers
Real estate investment professionals
Building operations managers
Property portfolio managers
Workplace and space management professionals
Project and development managers
Digital transformation and smart building professionals
Executives responsible for property and facilities strategies
Target Competencies
Participants will develop competencies in:
AI in real estate
AI-enabled facilities management
Real estate analytics
Predictive maintenance
Smart building technologies
Space and occupancy analytics
Property data management
Digital twins and IoT
Generative AI for property operations
AI implementation and governance
