AI for construction work - You will learn how to apply AI to real construction tasks so you can review data faster, reduce mistakes, and support better decisions during tendering and project delivery.
Faster tender document review - You will learn how to summarize tender documents quickly, spot participation requirements and risks, and build checklists that keep your bid preparation structured and clear.
Quicker bidding workflow - You will see how AI can help you draft RFQs, review quantity takeoffs, and compare subcontractor offers, making it easier to collect and evaluate bid data efficiently.
Stronger estimating support - You will practice reviewing takeoffs and work scope, identifying missing items, and preparing inputs for cost estimates, so you can catch gaps before submitting an offer.
Better project execution control - You will discover how to use AI for site reports, progress tracking, daily planning, and trade coordination, helping you maintain clearer control over project execution.
Effective prompting - You will learn how to write precise prompts, structure requests effectively, and avoid common mistakes, so AI gives you more accurate answers and more useful outputs.
Cleaner document handling - You will master working with PDFs, quantity takeoffs, and contracts, summarizing content and finding key information faster to create practical checklists and procedures.
Safe use of AI - You will understand AI limits, the risk of overinterpreting data, legal responsibility, and good usage practices, so you can apply these tools with greater confidence and care.
AI in construction is presented through its practical operating logic rather than theory alone. The section explains what AI is, how it works in day-to-day use, and where it brings the most value across the investment process from an organizational perspective.
Tender decisions depend on quickly extracting key requirements from SWZ documentation. Participants practice summarizing the documents, identifying participation conditions and risks, and building tender checklists that support a more disciplined bid qualification process.
Creating subcontractor RFQs can be standardized when AI links quantity takeoff analysis with communication and comparison tasks. The section shows how to prepare enquiries, work with the bill of quantities, and compare incoming offers in a structured manner.
Cost estimating work often starts with checking whether the scope is complete and measurable. Here AI supports the analysis of bills of quantities, helps detect omissions, and assists in preparing the cost estimate on the basis of more consistent source data.
On active projects, AI can support coordination by structuring construction site reports and interpreting progress data. It is also used to organize the daily plan and improve interdisciplinary alignment, helping teams track execution and respond to emerging issues.
Effective results depend first on how questions are written. Participants learn the structure of a strong prompt, how to formulate instructions for AI clearly, and which common mistakes lead to vague, incomplete, or misleading answers in construction-related tasks.
PDF files, bills of quantities, and contracts become easier to process when AI is used for targeted analysis. The section covers summarization, information retrieval, and turning document findings into checklists and procedures that support repeatable project work.
To reduce repetitive manual work, participants build reusable prompts and structured query templates for tasks such as RFQ preparation or SWZ analysis. The focus is on embedding AI into everyday office and site workflows in a consistent, controllable way.
Reliable AI use in construction requires clear boundaries. This part addresses data overinterpretation, legal responsibility for AI-supported outputs, and practical rules that reduce risk when models are used in operational, analytical, and decision-support tasks.
Basic construction process knowledge - You should understand the main stages of an investment project and know what tenders, project documents, cost estimates, and schedules are to follow the examples with ease.
Document handling skills - You should be able to read and navigate documents such as PDFs, quantity takeoffs, contracts, or summaries so you can find the information needed during practical exercises.
Basic computer skills - You should be comfortable using a computer, web browser, and text editor so you can complete tasks smoothly, write prompts, and work with the training materials.
Industry experience - You should have practical exposure to site office work, bid preparation, estimating, or coordination so you can easily connect AI tools with your own daily responsibilities.
