Course : Managing and Growing a Real Estate Business Using Artificial Intelligence

Turn your data into tools for performance, decision-making, and risk management

Practical course - 2d - 14h00 - Ref. AON
Price : 1680 CHF E.T.

Managing and Growing a Real Estate Business Using Artificial Intelligence

Turn your data into tools for performance, decision-making, and risk management


New course

Artificial intelligence provides executives, business leaders, and real estate managers with new capabilities to drive performance, analyze key metrics, optimize processes, and make more informed decisions. This training course provides a practical method for identifying high-value-added AI applications, leveraging business data, improving operational performance, and developing an AI roadmap tailored to your organization.


INTER
IN-HOUSE
CUSTOM

Practical course in person or remote class
Disponible en anglais, à la demande

Ref. AON
  2d - 14h00
1680 CHF E.T.




Artificial intelligence provides executives, business leaders, and real estate managers with new capabilities to drive performance, analyze key metrics, optimize processes, and make more informed decisions. This training course provides a practical method for identifying high-value-added AI applications, leveraging business data, improving operational performance, and developing an AI roadmap tailored to your organization.


Teaching objectives
At the end of the training, the participant will be able to:
Identify the opportunities and limitations of AI as applied to managing a real estate business
Leveraging business data to generate decision-making metrics
Identify processes that can be optimized or automated using AI
Assess the risks associated with the use of AI and define control measures
Developing an AI Roadmap Tailored to Your Agency, Department, or Organization

Intended audience
Real estate agency executives, branch managers, sales directors, network managers, real estate managers, property managers, building managers, commercial real estate marketing managers, and anyone involved in managing a real estate business.

Prerequisites
No specific knowledge required.

Practical details
A mix of methodological instruction, demonstrations, and feedback. Practical exercises conducted individually, in pairs, and in small groups. The training program is based on a core set of skills common to all real estate professions, enriched by case studies and exercises tailored to the specific characteristics of residential or commercial real estate, depending on the participants’ profiles.

Course schedule

1
Understanding Where AI Creates Value in the Real Estate Industry

  • Identify the concepts of AI, generative AI, and automation
  • Identify relevant uses by business line: transactions, management, property management, development, and commercial real estate
  • Distinguish between productivity, analytics, decision support, and automation applications
  • Assessing the Benefits and Limitations of AI in Real Estate Management
  • Identifying the Conditions for the Success of an AI Project in a Real Estate Organization
Hands-on work
Red Thread Case Study: Collaborative mapping of activities and processes that can benefit from AI. Residential: listings, appraisals, follow-ups, agency reporting / Commercial: B2B pipeline, occupancy, vacancies, space marketing, performance by site or sector.

2
Improving Sales and Operational Performance

  • Identify time-consuming activities with low value-added
  • Analyze operational issues affecting business operations
  • Using AI to Generate Summaries, Minutes, and Reports
  • Optimize sales follow-up, follow-ups, and team coordination
  • Prioritize actions based on their business impact, time savings, and feasibility
Hands-on work
Red Thread Case Study: Analysis of sources of time loss and opportunities for improvement. Residential: decline in listings, sales timelines, and seller follow-up / Commercial: vacant space, corporate inquiries, decline in occupancy, and account follow-ups.

3
Leveraging Data to Drive Business Operations and Inform Decisions

  • Identify the data relevant to managing a real estate business
  • Develop performance metrics aligned with the organization's objectives
  • Analyze business, financial, and operational trends using AI
  • Identify weak signals and opportunities for performance improvement
  • Produce decision-making summaries that managers and executives can use
Hands-on work
Case Study: AI-Assisted Analysis of a Business Dataset. Residential: prospects, listings, conversion rates, time to sale, revenue, customer satisfaction / Commercial: sales pipeline, occupancy rates, vacancy rates, revenue by square footage or by location.

4
Ensuring the Safe Use of AI and Managing Risks

  • Identify the operational, legal, regulatory, and reputational risks associated with AI
  • Verify the quality, reliability, and traceability of the data used
  • Apply the principles of personal data protection and regulatory compliance
  • Identify biases, errors, and illusions that could influence a decision
  • Establish a governance framework tailored to AI applications
Hands-on work
Red Thread Case Study: Risk Scenario Analysis. Residential: customer data, assisted estimates, excessive automation of a seller-buyer transaction, reporting errors / Commercial: company data, occupancy forecasts, confidential B2B information, unverified AI recommendations.

5
Creating an AI Roadmap to Grow Your Real Estate Business

  • Prioritize use cases that add significant value to the business
  • Identify the necessary resources, skills, and tools
  • Structuring a Phased Adoption Process: Testing, Pilot, Rollout
  • Define monitoring and return on investment metrics
  • Develop a short- and medium-term operational action plan
Hands-on work
Final presentation of the overarching case study: assessment, key indicators, identified risks, AI priorities, and roadmap. Residential: revitalization of a residential real estate agency / Commercial: improvement of sales performance, occupancy rates, or portfolio management for commercial properties.



This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.

Dates and locations

Dernières places
Date garantie en présentiel ou à distance
Session garantie
From 18 to 19 March 2027
FR
Remote class
Registration
From 24 to 25 June 2027
FR
Remote class
Registration
From 23 to 24 September 2027
FR
Remote class
Registration
From 9 to 10 December 2027
FR
Remote class
Registration

REMOTE CLASS
2027 : 18 Mar., 24 June, 23 Sep., 9 Dec.



This programme is an original creation, developed by the teaching teams at ORSYS Formation. Any reproduction, representation, adaptation or use, in whole or in part, without the prior written authorisation of ORSYS, is strictly prohibited. ORSYS reserves the right to take any action necessary to protect its intellectual property rights.