Webcor

Todd Mercer

There's a lot of buzz around generative artificial intelligence (AI) and large language models (LLMs) like ChatGPT. Construction companies need to develop digital/data strategies and change management programs to ease the introduction of this technology to our workflows. It isn’t the technology that limits us at this point; it’s the ability of our people to adapt to the accelerating pace of change.

LLMs can revolutionize the way we interact with computers and data. Anyone with an internet connection can easily access several powerful AI LLMs. The challenge lies in recognizing that this technology will change how we work. That change is already upon us and will only accelerate as generative AI evolves. How will we maximize its opportunities while minimizing risk to the organization?  

Odds are, you've heard of ChatGPT, the AI chatbot that can understand and generate human-like text. Introduced in late November 2022, ChatGPT has already become the fastest-growing online application in history. Two months after its launch, the OpenAI service had 100 million monthly active users, a milestone that took Google and Facebook five years and Instagram 2.5 years to achieve. Similarly, TikTok hit the 100-million milestone within nine months. This technology seems to be one of, if not the fastest-growing technology, with the potential for immediate penetration across all industries and businesses.  

So what is in store for us in the construction industry?

As builders, using generative AI and LLMs to analyze vast amounts of data will improve our efficiency and productivity through better decision-making, deeper collaboration, and improved communication. 

With the help of generative AI, construction professionals can access and analyze data quickly and easily, enabling us to make more informed and faster decisions. These tools can also improve communication between construction professionals and clients by translating technical jargon into easy-to-understand language, reducing misunderstandings, and enhancing collaboration. Specialized AI models may support technical tasks like code compliance reviews, engineering, and logistics optimization.

Companies will also turn these tools inward, allowing employees to use simple chatbot interfaces to extract information from internal documentation. These are just a few examples of how AI and natural language models will begin to change how we work, plan, and build our projects in the short term, ultimately delivering better outcomes.

Even though there are many benefits, there are also drawbacks to consider. LLMs can learn biases from their training data, leading to unfair or discriminatory outputs. They might need a deeper understanding of the content they generate, leading to errors or nonsensical responses. Generative AI models can sometimes overfit or produce unexpected outputs, raising concerns about the potential misuse of the technology. Other concerns include unethical uses (such as creating misinformation and deepfakes) and the fact that prompts containing proprietary information could be made public.

As the construction industry weighs the pros and cons of using ChatGPT and other forms of AI like Google's Bard, companies must decide how all tools fit into their overall digital strategy. Developing a plan for managing change and integrating these technologies into operations is crucial. Successfully deploying these tools relies on the technology and the human ability to adapt and use it.

Restricting or preventing their use is futile; employees will use these tools on their personal devices and port the results into their work. In addition, companies like Microsoft and Adobe have already begun integrating generative AI into their most popular software products. As a result, companies should prioritize their people and develop a robust change management strategy emphasizing effective communication and training. This will ensure all employees can leverage AI's tremendous capabilities to the company’s benefit while mitigating the risks.

The rapid evolution of generative AI presents both a significant opportunity and challenge for organizations. Those able to manage the change and integrate these technologies will reap the benefits, while those who fail risk falling behind. It all starts with cautious experimentation.