Global Learning for Operational Leaders
Course DIT-019
Artificial Intelligence (AI) in Real Estate Development and Facilities
Real estate and facilities teams generate data constantly, from building management systems, IoT sensors, work orders, o... The outline covers AI Applications Across the Real Estate and Facilities Lifecycle, AI for Real...
- 5 daysClassroom or online
- 14Upcoming dates
- 7Cities
- €1,925Fees from
Your week at a glance
- Day 1 AI Applications Across the Real Estate and Facilities Lifecycle
- Day 2 AI for Real Estate Development, Investment and Portfolio Decisions
- Day 3 Predictive Maintenance and Intelligent Facilities Management
- Day 4 Smart Buildings, Energy Optimization and Occupant Experience
- Day 5 AI Governance and Implementation for Real Estate and Facilities
Classroom
14 sessions
Scroll for more
Online / Live
14 sessions
Scroll for more
Introduction
Course overview
Real estate and facilities teams generate data constantly, from building management systems, IoT sensors, work orders, occupancy and leasing systems, yet decisions on maintenance, energy, space and new developments are still often made reactively or on instinct. This Aractech course shows where AI genuinely adds value across the property lifecycle and how to introduce it without losing control of cost, privacy or accountability.
The five days follow the asset from development to operation: AI-assisted market and feasibility analysis for new projects, portfolio and investment decision support, predictive maintenance for HVAC, lifts, pumps and electrical systems connected to CMMS, and smart-building use of BMS data, digital twins and occupancy analytics to cut energy use and improve the occupant experience. The final day covers data quality, cybersecurity, vendor selection, human oversight and how to measure return on investment.
Every day includes a workshop on a realistic property or facilities case, and participants finish by drafting an AI implementation roadmap for their own portfolio or facility, with priority use cases, required data, KPIs and governance.
What you will achieve
Learning objectives
- Map AI opportunities across development, investment, property management and facilities operations
- Apply AI-assisted analysis to market research, feasibility studies and development planning
- Design a predictive maintenance workflow linked to building assets and CMMS
- Use occupancy and space data to improve workplace planning and portfolio decisions
- Identify AI-driven energy and HVAC optimisation opportunities
- Explain the role of BMS, IoT, digital twins and computer vision in smart buildings
- Assess data, privacy, cybersecurity and vendor risks before implementing AI
- Build an AI roadmap with measurable KPIs such as downtime, energy use and service response
Who should attend
Target audience
- Real estate development and project managers
- Property, asset and portfolio managers
- Facilities and building operations managers
- Real estate investment professionals
- Workplace and space planning professionals
- Smart building and digital transformation teams
- Executives responsible for property and facilities strategy
Methodology
Learning approach
- Instructor-led sessions on each stage of the property lifecycle
- Demonstrations of AI tools for analysis, maintenance and building performance
- Daily case studies and workshops on development, maintenance and smart-building scenarios
- Group evaluation of AI use cases by value, data readiness and risk
- Capstone AI implementation roadmap for each participant's portfolio or facility
Complete course outline
Five focused days of learning and application
The timings provided are estimates and may vary depending on the number of participants and the discussions taking place during the sessions. They are indicative only and do not constitute a binding commitment.
Day 1
AI Applications Across the Real Estate and Facilities Lifecycle
- Understanding artificial intelligence, machine learning, generative AI, predictive analytics, and computer vision in a property context
- Mapping AI opportunities across real estate development, investment, asset management, property management, and facilities operations
- Identifying data sources including property systems, maintenance records, BMS, IoT sensors, occupancy systems, financial data, and external market information
- Understanding how AI converts property and operational data into predictions, recommendations, automation, and decision support
- Coffee break
- Understanding how AI converts property and operational data into predictions, recommendations, automation, and decision support (continued)
- Evaluating AI use cases according to business value, data availability, implementation complexity, operational impact, and risk
- Practical exercise: Building an AI opportunity map for a real estate portfolio or facilities management operation
Day 2
AI for Real Estate Development, Investment and Portfolio Decisions
- Applying AI-assisted research to market analysis, location assessment, property demand, and development opportunities
- Using predictive analytics and scenario modelling to support feasibility studies and development planning
- Applying AI to property portfolio analysis, asset performance monitoring, and investment decision support
- Using generative AI to analyze development documents, reports, proposals, contracts, and project information
- Coffee break
- Using generative AI to analyze development documents, reports, proposals, contracts, and project information (continued)
- Exploring AI applications in construction progress monitoring, project risk identification, cost information, and development reporting
- Case study: Evaluating a real estate development opportunity using AI-supported market, financial, operational, and risk information
Day 3
Predictive Maintenance and Intelligent Facilities Management
- Moving from reactive and preventive maintenance toward predictive and condition-based maintenance strategies
- Using equipment history, sensor data, alarms, work orders, and failure patterns to identify maintenance requirements
- Understanding AI applications for HVAC, electrical systems, lifts, pumps, and other critical building assets
- Coffee break
- Understanding AI applications for HVAC, electrical systems, lifts, pumps, and other critical building assets (continued)
- Connecting AI analytics with Computerized Maintenance Management Systems (CMMS) and facilities management workflows
- Applying generative AI to maintenance records, work-order summaries, troubleshooting knowledge, and facilities documentation
- Practical workshop: Designing an AI-enabled predictive maintenance workflow for critical building equipment
Day 4
Smart Buildings, Energy Optimization and Occupant Experience
- Integrating AI with Building Management Systems (BMS), IoT devices, smart meters, sensors, and connected building infrastructure
- Using occupancy analytics to improve space utilization, workplace planning, cleaning schedules, and building services
- Applying AI to energy consumption analysis, HVAC optimization, demand patterns, and building performance improvement
- Coffee break
- Applying AI to energy consumption analysis, HVAC optimization, demand patterns, and building performance improvement (continued)
- Understanding digital twins and their role in monitoring, simulation, asset information, and facilities decision-making
- Exploring computer vision and intelligent monitoring applications while considering privacy and appropriate controls
- Case study: Developing an AI-supported smart building strategy for energy efficiency, space utilization, and occupant experience
Day 5
AI Governance and Implementation for Real Estate and Facilities
- Assessing data quality, interoperability, system integration, and information ownership before implementing AI solutions
- Managing privacy, cybersecurity, access controls, sensitive building information, and third-party technology risks
- Coffee break
- Evaluating AI vendors and solutions based on business requirements, integration capability, scalability, transparency, and total cost
- Establishing human oversight and validation for AI-generated predictions, recommendations, and operational decisions
- Measuring AI performance through maintenance cost, downtime, energy consumption, space utilization, service response, tenant experience, and return on investment
- Capstone exercise: Developing an AI Implementation Roadmap for Real Estate Development and Facilities covering priority use cases, required data, technology integration, governance, KPIs, and expected business value
Course FAQs
Questions about this course
What participants and training managers usually ask before booking Artificial Intelligence (AI) in Real Estate Development and Facilities. Can't find your answer?
What does Artificial Intelligence (AI) in Real Estate Development and Facilities (DIT-019) cover?
This course covers Digital Innovation and Transformation through a structured five-day outline focused on practical application, discussion, and implementation planning.
When is the next available session?
The next scheduled session starts on 9 - 13 November 2026. See the course schedules section for the available dates and delivery formats.
Who should attend this course?
Real estate development and project managers, Property, asset and portfolio managers, Facilities and building operations managers
Is bilingual course delivery available?
Yes. All course materials and presentations are provided in English, while bilingual explanation and discussion support may be available depending on the selected location and trainer availability. For example, when attending a course in Istanbul, you may request a Turkish-speaking trainer to explain the English course content in Turkish. Arabic explanation support may also be requested at this location. Other languages are available in selected cities. You can choose your preferred language support as an optional preference during registration.
How can I register for a session?
Use any Register button next to the available course dates to open the participant registration page and submit your booking request for the selected session.
Is this course available online as well as classroom-based?
Check the course schedules section for currently published classroom and Online / Live sessions.
Where are classroom sessions delivered?
Current classroom venues include Amsterdam, Istanbul, Rome, Kuala lumpur, Barcelona, London, Geneva.
How long is the training programme?
The programme runs for five days from 09:00 to 14:00, which gives 25 contact hours, including a daily 30-minute break (22.5 hours of instruction).
Quick request
Send quick request
Send a fast enquiry about this course and the academy team will get back to you.
Get a quotation
Request a formal quotation
Choose an available date and venue, add your participants, and we will email a formal quotation for Artificial Intelligence (AI) in Real Estate Development and Facilities to your business address.