Regenerative AI can improve efficiency, productivity and work quality in the construction industry. AI tech is rapidly evolving, creating countless new opportunities in every industry.

A new form of generative AI is emerging that uses continuous learning. How can it help construction professionals?

 

Applications of Regenerative AI in Construction

Regenerative AI is an emerging niche type of AI that blends generative AI and machine learning. It uses continuous learning to adapt both before and after launch. In contrast, typical generative AI algorithms do all of their training upfront and need manual updates to learn anything new afterward. There are a few ways construction pros can use this tech.

 

Back Office Automation

One of the best uses for regenerative AI in construction is back office automation. Generative AI algorithms like ChatGPT can automate daily office tasks like drafting emails, analyzing reports, organizing spreadsheets and more.

Automating these tasks can help construction companies address labor shortages by improving back office efficiency. The Associated Builders and Contractors estimates the industry is short at least 500,000 workers as of 2023. Construction companies need to optimize for efficiency in every way possible, including in the office. Using AI to automate repetitive tasks allows the office to function with fewer employees.

Generative AI can also automate some communication tasks through natural language chat bots. This might not be ideal for conversing with stakeholders, but chatbots can help with repetitive types of conversations. For example, employees who need to call off sick can report it through a chatbot that automatically files a time off request for them.

Stakeholder Materials Generation

Getting stakeholders on board with a construction project usually requires important materials like concept art and proposal documents. It can be expensive and time consuming to create all of these materials manually, though. Regenerative AI may be able to help construction and architecture firms create stunning concept art with less time and resources.

Generative AI can be combined with BIM programs to generate building artwork based on the technical specifications of a structure. This gives stakeholders the most accurate concept art possible so they can establish reasonable expectations and suggest changes wisely. Regenerative AI will continue learning as it creates more concept art so it improves in quality over time.

Construction teams can even use AI to analyze geological data and highlight key features in terrain imaging. Modern AI can comprehend data from traditional camera images as well as advanced LiDAR imaging. Both types of visuals are invaluable for helping stakeholders understand the terrain the structure will be built on.

AI has proven adept at handling text-based content, which makes it great for tasks like drafting emails and stakeholder correspondence. Many of the proposals and legal documents stakeholders need can be lengthy and technical yet contain similar information. AI can learn how these documents work and generate drafts to fit desired formats.

Using AI to create the first drafts of emails and other documents can save time, resources and money. It can also be helpful for construction professionals who understand the industry but may not feel confident in their writing skills. The AI can give them a basic literary foundation that can help their writing appear more professional to stakeholders.

 

Architectural Idea Generation

Architectural design needs to evolve to meet today’s sustainability needs. Generative AI can help architects brainstorm and boost their creativity. For instance, a generative AI could suggest ways to incorporate sustainable materials in a new building design. An architect could ask for suggestions specific to almost any need and the AI could generate something to match.

Of course, not all suggestions from a generative AI will be usable. That’s not the idea, though. The goal is to get the ball rolling and help designers think outside the box. The data-driven nature of AI means that algorithms will often generate results a human wouldn’t typically think of.

 

Challenges of Regenerative AI in Construction

Regenerative AI is an exciting development in construction tech, but it isn’t without a few risks. Industry professionals should be aware of these potential drawbacks before investing in this technology.

For example, generative AI is great for rapidly creating artwork, but may pose copyright risks. Some art generation algorithms don’t ask for artists’ permission before using their work in training datasets. This can lead to intellectual property infringement and legal issues. Carefully research any art generation AI before using it and confirm that the algorithm was trained on legally obtained artwork only.

Additionally, generative AI is still in its early stages. As a result, algorithms do struggle with inaccuracies and “hallucinations” from time to time. An AI hallucination occurs when the algorithm makes an incorrect connection or creates false information. Both of these issues can be resolved by simply proofreading any AI-generated content.

 

The Future of Construction AI

The construction industry is undergoing a widespread digital transformation. AI is becoming a central part of that wave of innovation, bringing opportunities for optimization and productivity gains. Regenerative AI can help construction pros improve the quality of their work, automate back office tasks and offer a better experience for stakeholders.