Better decision-making in construction with data and AI

The construction industry generates vast amounts of data, but this data is rarely used in new construction and renovation projects. The Integrated AI for Decision Support in Construction project explores how artificial intelligence can turn insights from existing buildings into better decisions and more accurate risk assessments.

Artificial intelligence is playing an increasingly important role in the digital transformation of the construction industry.

More and more companies are incorporating AI into their work, and interest in using data more systematically is growing as demands relating to quality, cost efficiency and sustainability increase.

Nevertheless, only a fraction of the knowledge already contained in the construction industry’s extensive data is being used. This is precisely the potential that the project sets out to explore.

“Today’s design process requires many decisions to be made at an early stage of a construction project, and these decisions have a major impact on the building’s performance. However, decisions are often based on previous experience rather than on collected data. We hope that our project can help shed light on how AI can be used as an active partner to support decision-making in the early stages,” says Mads Dines Petersen, project manager and associate professor on UCN’s construction programmes.

Turning data into knowledge

The construction industry generates vast amounts of data throughout the entire life cycle of a building, from initial analyses and design choices to operation, maintenance and renovation.

Much of the knowledge gained remains tied to the individual building and therefore rarely benefits future projects. The project examines how artificial intelligence and machine learning can connect data from different stages of the construction process, allowing existing knowledge to be put to use in new ways.

“We hope to demonstrate that the data we collect can be used strategically to support decision-making and help improve construction projects,” explains Mads Dines Petersen.

AI and building operation data will provide clients with a stronger basis for making decisions and assessing risks.

The project is based on anonymised building operation data provided by housing associations. The data includes information on maintenance, repairs and recurring issues in the buildings.

AI is used to analyse patterns and relationships in the data in order to determine whether insights from existing buildings can help predict potential challenges in future projects.

In this way, data becomes more than simply a record of the past. It becomes a tool for informing future choices.

AI as decision support

The construction industry increasingly regards artificial intelligence as a tool for supporting analysis, planning and decision-making. At the same time, several studies indicate that considerable untapped potential remains when it comes to turning the industry’s data into tangible value.

The project aims to investigate whether a data-driven model can reveal relationships between technical building choices, operational experience and financial consequences, as well as how such a model can be applied in practice.

This could provide clients and consultants with a stronger basis for assessing risks and prioritising resources in the early stages of a project.