The proliferation of artificial intelligence is reshaping how the architecture, engineering, and construction sector operates as firms grapple with the rapidly evolving capabilities of these systems. Finding an appropriate blend of humanity and machinery is key to ensuring not only the security of engineering outcomes but of engineering jobs as well.
As in many sectors of the economy, AI is transforming the business and practice of engineering. While certain AI-powered models have been around for years, engineers only recently have begun to rely on such systems for their day-to-day work. This reliance is expected to increase. According to a recent survey – the 2024 State of Design & Make report from Autodesk Inc. – two-thirds of AEC leaders believe AI will be essential in the daily operations of their firms in the next few years.
Further reading:
- What do civil engineers need to know about artificial intelligence?
- Artificial intelligence detects fires early, protecting people and infrastructure
- How AI is changing civil engineering right now
For many in the AEC world, the attitude toward AI is: “Use it now!” But engineering leaders should avoid rushing to adopt the technology across their workflows just because everyone else is doing it. Without the right governance and quality controls for AI, those firms will put their own reputation at risk as well as the reputation of engineering overall. They need to acknowledge that only the collective energy and efforts of AEC leaders throughout the industry will ensure the long-term success of AI platforms in this sector.
Many firms recognize that AI is an incredibly useful tool, capable of performing multiple complex calculations at once. Its processing and pattern recognition capabilities can create models in a flash that might otherwise take spreadsheet-armed humans hundreds of hours to do.
At the same time, the use of AI could fundamentally change the economics of countless engineering firms, disrupting their business models and potentially replacing labor hours with data-driven digital outcomes. As a result, AI could shift how engineering firms monetize their expertise and services.
For example, engineers traditionally bill their clients for the hours spent on tasks such as creating models and generating blueprints. But if an AI system can complete in a few minutes what previously took several engineers many hours to accomplish, the industry’s existing way of doing business will become obsolete.
Today’s AEC industry is grappling with a set of dueling pressures: keeping up with competitors while protecting job security and performance integrity. The use of AI only increases that pressure, as firms that don’t explore and adopt this new technology risk missing the boat badly, while those that do turn to technology could likewise threaten jobs and slash their firms’ revenues.
That’s why efforts to involve engineers in digital delivery must strike a balance between human needs and computing efficiencies. The good news for all engineers is that their jobs involve more than just routine calculations. Instead, engineers work with an untold number of variables to understand long-term cause and effect, bringing creativity and synergy to their projects in order to succeed.
So, the key to optimizing and protecting the engineering field is to capitalize on this human effectiveness, mixing it with the speed and power of digital technology. Because this will represent a new and different role for engineers, their firms will likely need to restructure to deal with such changes. For example, if AI takes over much of the day-to-day work that engineers traditionally perform, the engineers will have to operate at a higher level, overseeing the outcomes and calculations performed by AI systems.
At the same time, the number of “junior engineers” will likely decline in favor of engineers who become technology managers with hybrid skills. Such engineers will need the technical proficiency to operate effectively as “translators” for AI, working in a world in which understanding AI systems will be almost as important as understanding engineering itself. Consequently, engineers who also bring some degree of computer science knowledge to the table will be best prepared for success.
Although AI clearly is changing some of the traditional work performed within AEC firms, those firms need to be discerning about what digital systems they deploy. Rather than relying too much on black box technologies, the smartest firms will keep human engineers at the center of their efforts and provide detailed visibility into how they develop their engineering solutions. Finding the right balance between intelligently deployed AI models and the essential intervention and interpretation of human beings is the key for AEC firms that plan to stay ahead of their competition.
