14DEC
14 - 18 Dec 2026Mon to Fri · 5 days
IstanbulTurkey · Classroom
£2,850per delegate2+ people: £2,280 each
Professional training 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, occupancy and leasing systems, yet decisions on…
- 5 daysClassroom
- 13Upcoming dates
- 7Cities
- £2,250Fees from
Course overview
Why Attend
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 LLMI 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.
Course 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
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
Course Methodology
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
Course outline
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1Day 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
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
-
2Day 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
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
-
3Day 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
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
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4Day 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
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
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5Day 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
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
Schedule
Dates and fees
13 upcoming dates in 7 cities. Fees are per delegate; bring colleagues and every seat is discounted.
December 2026
IstanbulTurkey · Classroom
January 2027
18JAN
18 - 22 Jan 2027Mon to Fri · 5 days
RomeItaly · Classroom
£4,250per delegate2+ people: £3,400 each
February 2027
15FEB
15 - 19 Feb 2027Mon to Fri · 5 days
Kuala LumpurMalaysia · Classroom
£2,250per delegate2+ people: £1,800 each
March 2027
15MAR
15 - 19 Mar 2027Mon to Fri · 5 days
BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
April 2027
19APR
19 - 23 Apr 2027Mon to Fri · 5 days
LondonUnited Kingdom · Classroom
£4,200per delegate2+ people: £3,360 each
May 2027
17MAY
17 - 21 May 2027Mon to Fri · 5 days
GenevaSwitzerland · Classroom
£5,250per delegate2+ people: £4,200 each
June 2027
21JUN
21 - 25 Jun 2027Mon to Fri · 5 days
AmsterdamNetherlands · Classroom
£4,250per delegate2+ people: £3,400 each
July 2027
19JUL
19 - 23 Jul 2027Mon to Fri · 5 days
IstanbulTurkey · Classroom
£2,850per delegate2+ people: £2,280 each
August 2027
16AUG
16 - 20 Aug 2027Mon to Fri · 5 days
RomeItaly · Classroom
£4,250per delegate2+ people: £3,400 each
September 2027
20SEP
20 - 24 Sep 2027Mon to Fri · 5 days
Kuala LumpurMalaysia · Classroom
£2,250per delegate2+ people: £1,800 each
October 2027
18OCT
18 - 22 Oct 2027Mon to Fri · 5 days
BarcelonaSpain · Classroom
£3,850per delegate2+ people: £3,080 each
November 2027
15NOV
15 - 19 Nov 2027Mon to Fri · 5 days
LondonUnited Kingdom · Classroom
£4,200per delegate2+ people: £3,360 each
December 2027
20DEC
20 - 24 Dec 2027Mon to Fri · 5 days
GenevaSwitzerland · Classroom
£5,250per delegate2+ people: £4,200 each
No dates in this city right now. Request a quotation and we will suggest the nearest date.
Questions
Frequently asked questions
How long is the Artificial Intelligence (AI) in Real Estate Development and Facilities course?
The course runs over 5 days of classroom training, usually Monday to Friday.
When is the next Artificial Intelligence (AI) in Real Estate Development and Facilities course?
The next public date is 14 - 18 Dec 2026 in Istanbul. There are 13 upcoming dates in total.
Where is this course held?
Upcoming sessions run in Istanbul, Rome, Kuala Lumpur, Barcelona, London, Geneva, Amsterdam.
How much does the course cost?
Fees start from £2,250 per delegate, depending on the city. Fees include tuition and course materials.
Do participants receive a certificate?
Yes. Delegates who complete the course receive a London Leadership Management Innovation certificate of completion.
Can this course be delivered in-house for our team?
Yes. LLMI can tailor and deliver this course privately for your organisation at your premises or in one of our training cities.
Course information last updated 14 November 2026.
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