The construction industry is on the brink of a technological revolution, and artificial intelligence (AI) is the driving force. Once viewed as science fiction, AI is now reshaping traditional construction workflows, promising levels of efficiency and precision that were previously out of reach.
To navigate this evolving landscape and go beyond the hype, industry leaders must look past buzzwords to understand AI’s real-world implications, its current influence, and future capabilities. By grasping these aspects, businesses can effectively leverage AI to elevate their performance and stay ahead in an increasingly competitive market.
Types & Key Components of AI
Some of AI’s most common applications include:
- Personalized article recommendations commonly found on websites
- Tailored show and movie suggestions that appear on streaming platforms
- Spam filters that keep unwanted emails out of your inbox
- Answers you receive from smart devices
- Fraud detection algorithms that protect your credit card transactions
- Real-time traffic updates in navigation apps
- Voice-to-text transcription features in your smartphone’s keyboard
There isn’t just one universal brand of AI that fuels these applications; however, there are two main types of AI, which are then further segmented into three primary categories.
Narrow (or Weak) AI
Narrow AI is designed to perform specific tasks within a defined context — think of it as a specialist. For example, software that recognizes faces in photos or a chatbot that answers customer service inquiries.
Narrow AI is what we encounter most in our daily lives, both personally and professionally. It does not possess general intelligence or consciousness and therefore is incapable of transferring its learning to new situations and other domains.
General (or Strong) AI
This is the AI of science fiction (so far) — a theoretical system with human-like intelligence across a wide range of domains. It would be capable of understanding, learning, and applying knowledge in ways similar to humans. While researchers are actively working toward this goal, true general AI remains elusive.
During the general session at CFMA’s 2024 Annual Conference & Exhibition, James Benham, Co-Founder and CEO of JBKnowledge, estimated that this level of AI is still 30 years away.1
Three Primary AI Subsets
Machine Learning
Machine learning focuses on algorithms that enable computers to learn from data with explicit programming. By analyzing vast data sets, machine learning algorithms can do a lot of what we’ve defined previously — identify patterns, make predictions, and improve their own performance over time. As such, machine learning is the backbone of many current AI applications.
Deep Learning
Deep learning utilizes artificial neural networks with multiple layers to mimic the structure of the human brain. This enables the processing of complex data (e.g., image and speech) with remarkable accuracy.
Deep learning powers technologies like facial recognition, self-driving cars, and language translation.
Natural Language Processing
Natural language processing (NLP) focuses on enabling computers to understand, interpret, and generate human language. It is crucial for applications like chatbots, virtual assistants, and sentiment analysis tools, which aim to bridge the gap between human communication and machine understanding. Within NLP are large language models (LLMs) like ChatGPT that generate human-like text.
Now that we’ve laid the groundwork for understanding AI and its various forms, let’s shift gears to focus on its potential for revolutionizing the construction industry.
The Projected Impact of AI in Construction
From project plans and blueprints to material specifications and sensor readings as well as contracts and financial statements, the construction industry is teeming with valuable information waiting to be unlocked. AI offers the key to extracting insights from this data, enabling construction companies to optimize processes, enhance safety, improve decision-making, and ultimately drive greater efficiency and profitability.
From a financial standpoint, the potential impact of this AI-driven transformation is staggering. Globally, the construction industry is worth more than $10 trillion annually2 and constitutes 13% of the world’s gross domestic product.3 McKinsey estimates that embracing digitization (including AI-powered technologies) could enhance construction’s market capitalization by $1.6 trillion yearly, in addition to accelerating its year-over-year labor productivity growth (which currently lags 2% behind the total world market’s growth rate; see Exhibit 1).4
This data makes a compelling case that adopting AI is not merely beneficial for companies; it’s essential for the construction industry to keep pace and remain competitive with other markets in future years.
AI on the Rise
Though the construction industry is traditionally slower to adopt new technologies, there is a growing recognition of the benefits of AI and other modern technologies. In fact, a recent report shows that over a quarter of construction business owners, GCs, and specialty contractors are already using AI or machine learning technologies, and an additional 30% plan on adopting these technologies within the next year.5
The report further suggests that advancements, like refined LLMs, will spur greater AI adoption.6 Mordor Intelligence’s research supports this claim, forecasting the growth of AI’s market share in construction from $3.02 billion in 2023 to $11.85 billion by 2029 at a compound annual growth rate of 24.31% (Exhibit 2).7
This gradual adoption of AI signals a turning point for the construction industry, demonstrating that companies are not just adapting to the current challenges; they’re positioning themselves for a more resilient and efficient future.
A Catalyst for Change
The drive to adopt AI in construction is fueled by its potential to address the very challenges that are plaguing the industry. Supply chain disruptions, rising material costs, and increasingly complex projects have intensified the need for innovative solutions, with 32% of construction stakeholders reporting that advanced technologies are crucial for tackling these issues head-on.8
Workforce development is another huge problem in construction, now extending to include the accounting function. A 2023 Wall Street Journal article shines a light on some alarming trends:
- The number of accounting graduates in the U.S. with either a bachelor or master’s degree dropped 7.4% to 65,305 in the 2021-22 academic year, which is the largest single-year drop experienced in the industry since the 1994-95 academic year (Exhibit 3).
- Between 2019 and 2022, there were 15.9% fewer accountants in total.
- According to data from the U.S. Bureau of Labor Statistics, over 300,000 accountants quit their jobs between 2019 and 2021.
- Data from the U.S. Bureau of Labor Statistics shows a 15.9% drop in auditors in the U.S. since 2019.9
These statistics underscore the urgent need for solutions that enable the industry to do more with less, improve efficiency, and alleviate heavier workloads that current accountants may be experiencing due to the declining workforce. AI presents a promising avenue to address these challenges.