Transformative, revolutionary, game-changing, and astounding are all words to define Artificial Intelligence (AI). AI is now permeating our daily lives, although the rapid evolution of this technology and its implications remain a mystery for many. Recent advances in AI and its applications are not only working
themselves into our everyday personal lives but in the business realm too. This includes the construction industry.  

AI provides an opportunity to improve performance and outcomes in both the present and future of construction. This Guide explores artificial
intelligence through that lens, providing a foundational understanding of AI, its evolution, and its current and future uses in the construction industry.

“The adoption of AI has doubled in the past five years. It is a tool and skill for the present and the future.”

Artificial intelligence is not new. Humans have been trying to incorporate
human-like intelligence into machines for decades, which remains a driving motivation behind the advancing capabilities of artificial intelligence.

You most likely have already had AI present in some of your daily
activities, perhaps without even knowing about it. For example, in the early 2000s, search engine pioneer Google put machine learning to work for its
online advertising and to improve the accuracy of search engine results.

Artificial intelligence refers to the ability of machines to perform tasks that
usually require human intelligence, such as understanding a natural language, recognizing images, and making decisions. Human intelligence revolves around the capacity to acquire information and apply it to situations and skills.

Artificial Intelligence is defined as a field in data science that blends computer technology with substantial amounts of data to enable problem-solving. AI is a broad field with several subfields -- such as machine learning (ML) and deep learning (DL).

In relation to construction, AI supports tasks such as planning and organizing and making the physical demands of building easier. Some examples include robotic heat welders, remote-controlled demolition robots, and AI-assisted takeoff solutions.

AI in the construction industry is at a pivotal time. AI is poised to become more prominent in daily construction activities, much like it already is in the healthcare, financial services, and entertainment industries. AI can provide construction professionals the competitive edge they need to
improve their productivity, efficiency, and generate more profitable bids.

ConstructConnect’s AI-assisted estimating software, Takeoff Boost®, can help you save time and money – without compromising accuracy. Request your free demonstration to learn how we can help you estimate, bid, and win more projects.  

Algorithm: A set of specific instructions designed to achieve a predetermined goal.

Artificial Intelligence (AI): A field in data science that blends computer technology with substantial amounts of data to enable problem-solving. AI involves computers and systems that learn from experience to make machines do things humans do, only better and faster. 

Automation: Technology that performs tasks with a device or system and reduces human input.

Building Information Modeling (BIM): A digital model of a building accurately represented in a digital format. BIM can represent the entire building lifecycle from design and planning through construction, maintenance, and end-of-use.

Cognitive Computing: A type of AI that is designed to simulate human thought processes, using techniques like natural language processing and machine learning to analyze and
understand complex data.

Computer Vision (Visual Recognition): A field of AI that
focuses on enabling machines to interpret and understand
visual data and includes tasks like object recognition, facial
recognition, and image grouping.

Deep Learning (DL): A subset of AI that uses artificial neural
networks to process substantial amounts of data and solve problems with limited human help. 

Digital Twin: A digital replica of a physical object like a building or HVAC (Heating, Ventilation, and Air Conditioning) system. Digital twins can be used for tasks like simulation, testing, and monitoring.

Generative AI: An approach to AI that involves training
algorithms to create new data that is like existing data, and is used to generate new images, text, or audio.

Image Recognition: The ability of a machine to identify
objects, people, or other features in digitalimages.

Human Intelligence: The thinking abilities typically associated with people, such as learning, reasoning, problem-solving, and creativity.

Machine Learning (ML): A subset of artificial intelligence that learns from experience, adapts, and improves performance without being explicitly programmed.

Natural Language Processing: The ability of machines to understand and analyze human language. This can include speech recognition, sentiment analysis to detect the emotion, intent or tone of messages, and language translation.

Robotics: A field of engineering that involves designing and building machines that can perform tasks autonomously or with little human interaction. Robotics often involves integrating AI technologies such as computer vision and natural language processing to carry out tasks.

Speech Recognition: The ability of machines to recognize and interpret human speech and is used for tasks like voice assistants, dictation, and transcription.