What is Artificial Intelligence & How Is It Revolutionizing the Construction Industry?

Technology is moving rapidly in the construction industry and is touching all areas of the ecosystem. From the digital transformation of the design process to new preconstruction estimation software, scheduling, predictive analytics, and asset management, new construction technology companies and startups are shaking up the industry at an exciting pace. With these new technologies and industry-wide digital transformation comes data – and lots of it.

And with lots of data, opportunities for AI emerge across the entire project lifecycle:

Artificial Intelligence: A Primer

Artificial intelligence (AI) leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind. It is a field that combines computer science, domain understanding, and robust datasets to enable automated predictions and problem-solving.

Today, a lot of hype surrounds AI, especially as to how it relates to applications in industry – whether it is in construction, healthcare, or manufacturing. There is significant enthusiasm for its potential for impact across every sector, and right now construction leaders are at the forefront of imagining “what is possible.”

As these discussions about imagining the possibilities for AI are occurring, there are also critical questions industry leaders and data scientists are asking regarding ethical considerations as well, ranging from privacy concerns to building systems that benefit society as a whole. 

Key Definitions

Within the AI space and applications for construction, three areas, in particular, are emerging as critically important to solving the industry’s biggest challenges: Data Strategy, Machine Vision, and Intelligent Document Processing.

Data Strategy is vital to every organization as it helps identify highly valuable data and connects this data to fulfilling the core objectives of the company.  This enables business leaders to manage data more like valuable assets – than byproducts of business activity – and it drives competitive advantage.

Data strategy is based on two dimensions: 1) Core business strategy, including goals and objectives; 2) The state of the business’ data assets. By understanding 1 and 2, a firm can devise a future state (“what success looks like”) and a roadmap for how to get there. Here are some examples of data strategy in action.

Machine Vision is the capability of a computer to visually perceive the environment. Immense amounts of images and video data are too time-consuming for humans to process. Machine vision leverages the latest technologies and methods to inspect and analyze visual data so it can be used in inquiries and controls, processes, and other applications reliant on accurate “sight.”  This includes object detection, object tracking, and activity tracking in both real-time and retrospective capacities, for a variety of purposes, including the following: project management, scheduling, health & safety, audit & compliance, and more. Learn more about machine vision here.

Intelligent Document Processing (IDP) is a new AI-driven approach to automating the categorization of documents, extracting data from documents, and creating documents. IDP is used to turn data from these documents, including unstructured data (text, video, images, and more) into a structured format for rapid and accurate processing and information retrieval and vice versa. An IDP model is tailored to the unique environment and document-handling needs of a particular organization.  IDP is actively applied in healthcare, financial services, insurance, supply chain, and legal industries today and has enormous potential for applications across the entire construction industry.