Artificial Intelligence (AI) in Real Estate Development and Facilities
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Course details

Artificial Intelligence (AI) in Real Estate Development and Facilities

Digital Innovation and Transformation 14 live dates
UPCOMING SEMINAR €3,400.- Get up to 50% Discount for Group Participants.
Venue Amsterdam - Netherlands
Date 9 - 13 November 2026
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Seminar content

What you will learn

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

Benefits

Why attend this seminar

  • Build current, practical knowledge in digital innovation and transformation.
  • Translate the course ideas into actions you can use immediately at work.
  • Review real schedule options across 15 venues and live dates.
  • Connect course detail, venue, and category routes in one workflow.

Methodology

How the course is delivered

  • Structured seminar input and guided discussion.
  • Applied examples using current business situations.
  • Focused explanations based on the stored overview and outline.
  • Clear next steps for implementation after the course.

Target audience

Who this is for

  • Professionals responsible for digital innovation and transformation.
  • Managers, specialists, and team leads who need applied skills.
  • Participants looking for a focused route into Artificial Intelligence (AI) in Real Estate Development and Facilities.

Seminar details

Detailed outline

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

  • 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

  • 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

  • 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

  • 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

  • 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

Dates and locations

Available seminar dates

50% DISCOUNT FOR GROUPS
14 dates
Date City Price
9 - 13 November 2026 25 CPD / CPE Credits / 5 days. €3,400.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
14 - 18 December 2026 25 CPD / CPE Credits / 5 days. €2,280.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
18 - 22 January 2027 25 CPD / CPE Credits / 5 days. €3,400.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
15 - 19 February 2027 25 CPD / CPE Credits / 5 days. €1,800.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
15 - 19 March 2027 25 CPD / CPE Credits / 5 days. €3,080.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
19 - 23 April 2027 25 CPD / CPE Credits / 5 days. €3,360.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
17 - 21 May 2027 25 CPD / CPE Credits / 5 days. €4,200.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
21 - 25 June 2027 25 CPD / CPE Credits / 5 days. €3,400.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
19 - 23 July 2027 25 CPD / CPE Credits / 5 days. €2,280.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
16 - 20 August 2027 25 CPD / CPE Credits / 5 days. €3,400.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
20 - 24 September 2027 25 CPD / CPE Credits / 5 days. €1,800.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
18 - 22 October 2027 25 CPD / CPE Credits / 5 days. €3,080.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
15 - 19 November 2027 25 CPD / CPE Credits / 5 days. €3,360.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now
20 - 24 December 2027 25 CPD / CPE Credits / 5 days. €4,200.- 2 participants: 20% discount 3 participants: 35% discount 5 or more participants: 50% discount Book now

Course certificate

Certificate awarded on completion

Every participant who completes this seminar receives a professional course certificate from INFORAMTECH.

  • Participants receive an INFORAMTECH certificate for completing Artificial Intelligence (AI) in Real Estate Development and Facilities.
  • The certificate recognises attendance and successful participation in the seminar.
  • It can support professional development records within digital innovation and transformation and related functions.
Verify a certificate

Information about

Frequently asked questions

When is my seat confirmed?

Your seat is confirmed once full payment has been received.

Do you offer group discounts?

Yes, we offer the following discounts for group bookings:

  • 2 participants: 20% discount
  • 3 participants: 35% discount
  • 5 or more participants: 50% discount
Can discounts be combined with other offers?

No, discounts cannot be combined unless explicitly stated.

What payment methods do you accept?

We accept bank transfers, credit/debit cards, and selected online payment methods.

When do I need to pay?

Full payment must be completed before the course start date to secure your participation.

Is VAT included in the course fee?

VAT treatment depends on your location and status:

  • EU Companies (with valid VAT number): VAT may be reverse charged (0%)
  • EU Individuals (without VAT number): VAT is applicable based on local regulations
  • Non-EU Participants: VAT is generally not applicable (0%)
Can I get a VAT invoice?

Yes, all participants receive an official invoice. EU companies must provide a valid VAT number.

Can I cancel my registration?

Yes, cancellations must be submitted in writing.

What is your refund policy?
  • More than 14 days before the course: Full refund
  • 7-14 days before the course: 50% refund
  • Less than 7 days before the course: No refund
Can I transfer my seat to another person?

Yes, substitutions are allowed at no extra cost if requested before the course start date.

What happens if the course is postponed or canceled?

We reserve the right to reschedule or cancel a course due to unforeseen circumstances. In such cases, you may:

  • Transfer to another date
  • Receive full refund
Will I receive a certificate?

Yes, all participants will receive a certificate of completion after attending the course.

Is attendance mandatory?

Yes, full attendance is required to receive certification.

Are your courses online or in-person?

We offer both in-person and virtual (live online) training options.

Will course materials be provided?

Yes, all participants receive training materials in digital format.

Are travel and accommodation included?

No, participants are responsible for their own travel and accommodation unless otherwise stated.

Can you deliver customized or in-house training?

Yes, we offer tailored training programs based on your organization's needs.

How can I contact you for support?

You can reach us via email info@informatech.uk or through our contact form. Our team will respond promptly.

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