Training course – AI Agents – Real Estate

AI Agents for Real Estate Professionals

Agentic AI for business teams: understand AI agents, automate workflows safely and keep control with human-in-the-loop and governance.

Duration
6 hours, one session
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

This course connects AI Agents with the everyday processes of Real Estate. Participants work on realistic scenarios and leave with prompts, workflows and checklists they can use straight away.

AI agents go a step beyond conventional chat assistants: they plan sub-tasks, use tools such as search, files or business applications and complete multi-step work largely on their own. In this compact course you will learn how agents are built, how they differ from chatbots and traditional automation, and which tasks genuinely justify their use. Widely used platforms serve as practical examples, including Microsoft Copilot Studio, custom GPTs and Claude with projects and tool connections.

In the hands-on sessions you design agent workflows for tasks from your own area of work, from triaging requests through research and drafting to handing results over to business systems. You decide where a person reviews and approves, which permissions an agent receives and how errors are detected. A dedicated block covers governance, data protection and accountability, so that your agents not only work but remain controllable, traceable and defensible within your organisation.

Much of the work in real estate revolves around documents: property listings, leases, service charge statements, minutes of owners' meetings, valuation reports and an endless stream of enquiries from prospects and tenants. Generative AI takes over the routine – drafting listings from key facts, summarising declarations of division and valuation reports, answering standard questions up front and structuring repair requests. AI agents connect the inbox, property database and scheduling into end-to-end workflows. For agents, property managers and asset managers this frees up time for viewings, negotiations and owner relations. What matters is handling tenant and owner data responsibly and having an expert check every legally relevant statement before it goes out.

The course is delivered live – either online in a virtual classroom or on-site in our training rooms in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run it exclusively for your team.

Who is this course for?

  • Estate agents and sales teams
  • Residential and block property managers
  • Asset and property managers
  • Developers and housebuilders
  • Staff at housing companies and cooperatives

Typical challenges we address

  • A high volume of recurring enquiries from prospects, tenants and owners
  • Time-consuming drafting of listings, letters and meeting minutes
  • Extensive lease and property documentation that must be grasped quickly
  • Data scattered across property management software, email and spreadsheets

What you will be able to do

  • You can explain how AI agents are structured and clearly distinguish them from chatbots and classic automation.
  • You can select a suitable agent platform for your requirements using transparent criteria.
  • You can design an agent workflow for a real process in your area and build a working prototype.
  • You can define human-in-the-loop checkpoints, test cases and escalation rules.
  • Produce listings, tenant letters and minutes with AI much faster and at consistent quality.
  • Analyse leases and property documents with AI in a structured way and review the results professionally.
  • Design simple automations for enquiries, repair requests and reporting across your portfolio.

Course outline

Module 1 What makes an AI agent
  • Agent building blocks: language model, instructions, knowledge, tools and memory
  • How agents differ from chatbots, macros and classic workflow automation
  • Levels of autonomy: from suggestion-making assistants to agents that act independently
  • Realistically judging which tasks suit agents and which do not
Module 2 Platform overview: Copilot Studio, GPTs and Claude
  • Microsoft Copilot Studio: agents grounded in company data and connected to Microsoft 365
  • Custom GPTs: configuring instructions, knowledge files and actions
  • Claude with projects, knowledge bases and tool access via the Model Context Protocol
  • Selection criteria: data access, integrations, administration and licensing
Module 3 Designing and building agent workflows
  • Breaking tasks into steps and defining hand-offs between agent and human
  • Writing system instructions, examples and knowledge sources for consistent output
  • Connecting tools: search, documents, email, spreadsheets and business applications
  • Building a prototype agent for a real process from your own area
Module 4 Human-in-the-loop, quality and error handling
  • Setting approval steps, escalation rules and thresholds for human review
  • Test cases, evaluation criteria and spot checks for quality assurance
  • Common failure modes: wrong tool choice, endless loops and fabricated facts
  • Using structured user feedback to improve the agent over time
Module 5 Governance, security and roll-out
  • Roles and responsibilities across business units, IT, data protection and works council
  • Least-privilege permissions, logging and protection against prompt injection
  • Positioning under the EU AI Act and GDPR: transparency, documentation and data flows
  • From pilot agent to production: operation, maintenance and measuring success
Module 6 Practice lab: Real Estate
  • Listings from key facts
  • Pre-qualifying enquiries
  • Minutes of owners' meetings
  • Summarising contract documents
  • Structuring repair requests
  • Market and owner reports
Module 7 Data protection, quality & transfer to daily work
  • Tenant, owner and prospect data falls under the GDPR, especially tenant self-disclosures and credit documents, and belongs only in approved AI environments. Legally relevant content such as contract clauses, mandatory listing details or resolution wording must be reviewed by a qualified person.
  • Ground rules for safe AI use in your team
  • Checking results: facts, sources, tests and the four-eyes principle
  • Personal action plan for the next 30 days
  • Open questions, outlook and resources for further learning

Practical scenarios from your field

Listings from key facts

Floor plans, location details and specification lists become compelling property descriptions in several tones and languages, which the team then reviews and completes with mandatory details such as energy performance data.

Pre-qualifying enquiries

An AI assistant triages incoming enquiries, answers standard questions about the property and documents, asks for missing details such as household size or financing status and proposes suitable viewing slots.

Minutes of owners' meetings

Notes or transcripts are turned into structured minutes with resolution wording, voting results and an action list, which the property manager checks before circulating and adding to the record of resolutions.

Summarising contract documents

Leases, declarations of division and valuation reports are condensed into key points such as terms, indexation clauses, exclusive use rights and maintenance obligations, speeding up due diligence and property handovers.

Structuring repair requests

Free-text tenant reports are classified by trade, urgency and property, enriched with follow-up questions and turned into draft work orders for contractors – including an acknowledgement to the tenant.

Market and owner reports

AI helps draft quarterly reports for owners and investors, summarising vacancies, letting activity and maintenance work from existing data and adding clear commentary on variances.

Prerequisites

You should already use an AI assistant such as ChatGPT, Copilot or Claude on a regular basis. No programming skills are required. Hands-on experience in property marketing, management or asset management; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser. Ideally you have access to at least one agent platform such as Copilot Studio, ChatGPT with GPTs or Claude; practice accounts can be provided if needed.

Data protection & compliance

Tenant, owner and prospect data falls under the GDPR, especially tenant self-disclosures and credit documents, and belongs only in approved AI environments. Legally relevant content such as contract clauses, mandatory listing details or resolution wording must be reviewed by a qualified person.

Dates & locations

For every location we suggest a date roughly four weeks ahead. Your preferred date is always possible.

  • Munich Tue, 15 December 2026 6 hrs Request
  • Salzburg Thu, 10 December 2026 6 hrs Request
  • Berlin Wed, 16 December 2026 6 hrs Request
  • Augsburg Fri, 11 December 2026 6 hrs Request
  • Hanover Tue, 15 December 2026 6 hrs Request
  • Bremen Tue, 15 December 2026 6 hrs Request
  • Stuttgart Fri, 11 December 2026 6 hrs Request
  • Kaiserslautern Thu, 10 December 2026 6 hrs Request
  • Online Mon, 14 December 2026 6 hrs Request

Frequently asked questions

Do I need programming skills to build AI agents?

No. The platforms used on the course rely on visual interfaces, plain-language instructions and ready-made connectors. You learn to specify agents precisely from a business perspective, connect tools and test workflows. Where deeper technical integration would be needed, you will know which requirements to put to your IT team.

Which platform will we use during the course?

The course is vendor-neutral and uses Microsoft Copilot Studio, custom GPTs and Claude as examples. You build your prototype on the platform that is available or planned in your organisation. The principles of workflow design, control and governance you learn carry over to other agent solutions as well.

How do I stop an agent from acting without control?

Through deliberate design: agents receive only the minimum permissions they need, critical actions such as sending, booking or deleting require human approval, and every step is logged. In addition, you define test cases and escalation rules. These are exactly the control mechanisms you develop for your own use case during the course.

Can I enter tenant data into an AI assistant?

Only in an environment approved by your organisation, backed by a data processing agreement and clear rules. In the course we show how to pseudonymise data, which information never belongs in public tools and how to work with placeholders without losing the benefits of AI.

Will AI replace agents and property managers?

No. AI handles drafting, triage and summaries. Viewings, negotiations, owners' meetings and legal responsibility stay with you. The gain lies in time freed up for client conversations and in faster, more consistent day-to-day processes. Error rates in routine correspondence also tend to fall.

How much does “AI Agents for Real Estate Professionals” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 6 hours of live training with a trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. For every location we suggest a date roughly four weeks ahead. In the request form you can always describe your preferred date or period in free text – we check availability and get back to you within one working day.

Is the course online or on-site?

Both are possible: live online in a virtual classroom or on-site in Munich, Salzburg, Berlin, Augsburg, Hanover, Bremen, Stuttgart and Kaiserslautern. We can also run the course exclusively for your team.

Can the course be tailored to our team?

Yes. Tailor-made courses cost approx. €4,500 more, depending on the topic and by arrangement. We agree content, examples and exercises with you in advance.

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