Training course · Generative AI · Construction & Architecture

Generative AI for Construction and Architecture

Vendor-neutral, hands-on day: how language models work, where they go wrong and how to roll out AI successfully in your team.

Duration
1 day (7 hrs)
Format
Online or on-site
Language
German or English
Participants
open dates or exclusive for your team
Certificate
Certificate of attendance

Overview

“Generative AI for Construction and Architecture” is a hands-on course for roles such as Architects, Civil and building services engineers and Site managers and project managers. Rather than learning Generative AI in the abstract, you work on tasks from your daily routine – with examples, exercises and templates from Construction & Architecture.

Generative AI has reached most organisations, yet teams often lack a shared understanding of what language models can actually do and where their limits lie. In this vendor-neutral course you will learn how large language models generate text, why they hallucinate and how careful prompting, context and source checking lead to reliable results. Rather than relying on any provider's marketing claims, you will work with transparent criteria that help you compare tools and judge their fit for your own tasks.

The second focus is everyday implementation. You will identify concrete use cases in your area of work, weigh benefit, risk and effort, and draft a realistic roll-out plan for your team. This covers ground rules for handling confidential data, a practical prompt library and ways to build acceptance and make results measurable. Throughout the day you work with examples from your own field, so you leave with an actionable roadmap rather than a set of abstract ideas.

Construction projects generate vast amounts of documentation: tenders, bills of quantities, specifications, minutes, snagging lists, variations, correspondence with authorities and standards. Architecture practices, engineering consultancies, contractors and clients spend a great deal of time on writing work that generative AI can speed up considerably. AI assistants help draft specification clauses, turn voice notes into site meeting minutes, structure variation claims, write competition and design statements and review extensive contract documents. Image-generating AI supports early design and visualisation stages. Professional and legal liability remains with designers and contractors – AI is a tool, not a substitute for knowledge of standards, structural engineering or site management.

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?

  • Architects
  • Civil and building services engineers
  • Site managers and project managers
  • Estimators and planners at contractors
  • Client representatives and public works departments

Typical challenges we address

  • Heavy documentation workload on site and in the office
  • Extensive bills of quantities, contracts and standards
  • Contentious variations, defects and delay notices
  • Skills shortages alongside rising design and sustainability requirements

What you will be able to do

  • You can explain clearly how language models generate text and why hallucinations occur.
  • You can write prompts that consistently deliver useful, verifiable results.
  • You can compare AI tools against transparent criteria covering data protection, features and cost.
  • You can identify and prioritise concrete use cases for your area of work.
  • Produce minutes, specifications and correspondence more efficiently with AI.
  • Analyse contract and project documents with AI in a structured way and spot risks earlier.
  • Use AI responsibly with due regard to liability, standards and confidentiality.

Course outline

Module 1 How large language models work
  • Tokens, context windows and probabilities: what happens when a model generates text
  • Training knowledge versus web search versus your own documents (RAG)
  • Text, images, audio and code: what multimodal models can do today
  • Realistically assessing typical strengths and weaknesses in office work
Module 2 Spotting hallucinations and getting reliable output
  • Why models produce plausible-sounding errors and when the risk increases
  • Prompting techniques: role, context, examples, output format and step-by-step instructions
  • Requesting sources, cross-checking facts and introducing a four-eyes principle
  • Scoping tasks so that AI assists rather than decides
Module 3 Choosing tools without vendor bias
  • Overview of chat assistants, AI built into office suites and specialist tools
  • Criteria: data processing, hosting location, admin features, integrations and pricing model
  • Enterprise licences, API access and locally hosted open-source models compared
  • Building a simple scoring matrix for your own tool selection
Module 4 Identifying use cases in your field
  • Systematically capturing recurring writing, research and analysis tasks
  • Rating benefit, risk and implementation effort for each use case
  • Distinguishing quick wins from strategic initiatives
  • Creating a prioritised use-case backlog for your team
Module 5 Rolling out generative AI in your team
  • Usage rules: which data may go into which tool and who signs off results
  • Building and maintaining a shared prompt library and templates
  • AI champions, training formats and peer exchanges to embed new habits
  • Measuring success: documenting time saved, quality and user satisfaction
Module 6 Practice lab: Construction & Architecture
  • Drafting specifications
  • Site meeting minutes
  • Variations and correspondence
  • Reviewing contract documents
  • Competition and design statements
  • Defects management
Module 7 Data protection, quality & transfer to daily work
  • Professional and legal liability for design, tendering and site supervision remains with the designer or contractor; AI output must be checked against standards, building regulations and contract terms. Public contracts are subject to procurement law and tender confidentiality, and copyright in designs must be respected.
  • 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

Drafting specifications

AI helps write clear and complete item descriptions for bills of quantities, spot gaps and contradictions and structure preliminaries – reviewed by the designer. Gaps are flagged for the designer.

Site meeting minutes

Voice notes and bullet points from site meetings or inspections become structured minutes with findings, responsibilities and deadlines, circulated to all parties. Photos are linked to each item.

Variations and correspondence

Delay notices, variation quotes, notices of concern and replies are prepared objectively and in line with the contract, with reference to the relevant contractual provisions.

Reviewing contract documents

Building contracts, special conditions and specifications are summarised for deadlines, liquidated damages, warranties and departures from standard terms, as a basis for legal review. Differences between contract versions are highlighted too.

Competition and design statements

Design concepts, sustainability strategies and project descriptions for competitions, planning applications or presentations are written concisely and tailored to different audiences. Length limits in competition briefs are respected.

Defects management

Defect reports are classified by trade and location, descriptions standardised and letters requesting remedial work with deadlines prepared. Progress stays transparent for site management and client alike.

Prerequisites

No technical background is required. It helps to bring along typical tasks from your day-to-day work that you would like to support with AI. Professional experience in design, construction or project management; no programming skills required.

Technical requirements

You will need a laptop with an up-to-date browser and internet access. A free account with a common AI assistant is sufficient; company licences are welcome.

Data protection & compliance

Professional and legal liability for design, tendering and site supervision remains with the designer or contractor; AI output must be checked against standards, building regulations and contract terms. Public contracts are subject to procurement law and tender confidentiality, and copyright in designs must be respected.

Suggested dates

All dates are suggestions – your preferred date is always possible.

  • Fri, 27 November 2026 Online Request
  • Tue, 1 December 2026 Augsburg Request
  • Mon, 14 December 2026 Online Request
  • Fri, 8 January 2027 Online Request
  • Fri, 15 January 2027 Kaiserslautern Request
  • Tue, 19 January 2027 Online Request

Frequently asked questions

Is the course tied to a specific AI tool?

No. The training is deliberately vendor-neutral. You work with widely used chat assistants and learn principles that apply to all major language models. That way you can transfer your skills to whichever tool your organisation has approved and evaluate new offerings yourself using clear criteria instead of relying on marketing statements.

How is confidential company data handled during the course?

For the exercises you use anonymised or fictitious examples from your area of work. At the same time you learn which categories of data may be entered into which tools, what to look for regarding data processing agreements and use of inputs for training, and how to set out these rules clearly for your team.

Will we leave with something concrete to implement?

Yes. You leave with a prioritised use-case backlog, a scoring matrix for tool selection, tested prompt templates and a draft set of team usage rules. These materials are designed so you can take them straight into internal discussions with management, IT and your data protection officer.

Can AI produce a bill of quantities?

AI can draft item descriptions, suggest structures and highlight gaps. Quantities, technical requirements and alignment with standards and design remain the responsibility of the designer, who is also liable. In the course you practise using AI as a drafting aid and reviewing results systematically.

Can drawings and plans be uploaded to AI tools?

Only if confidentiality agreements, copyright and your firm's policies allow it and the tool is approved. Strict requirements apply especially for security-sensitive buildings or public clients. The course shows how to work with approved solutions and sanitised documents. Project names and addresses can be removed beforehand.

How much does “Generative AI for Construction and Architecture” cost?

The course costs a flat €949 plus VAT per participant – whether online or on-site. This includes 1 training day(s) with a live trainer, course materials, a lab environment and a certificate of attendance.

Can I suggest my own date?

Yes. Our suggested dates are just a guide. In the request form you can always describe your preferred date or period in free text – we check availability and confirm 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 or Kaiserslautern. We can also run the course exclusively for your team.

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