This is a guest post by Markus Weidner
I’m pretty sure everyone has seen an attention-grabbing headline about how robotic process automation, machine learning (RPA/ML), and artificial general intelligence (AI) threaten our very existence. While this “new” raft of technologies is not new at all (large language models, for example, have been around for years), the very public realization about its impact and the hyperbolic howls of our human demise is noteworthy. This is not a flash-in-the-pan event.
Moreover, it’s wise to adopt a position where we accurately assess and estimate the potential for huge advances in several industries, including our own. For example, the rapid adoption of LLMs has already led to some people using RPA/ML learning to help cover periodic labor gaps and shortages. So it’s not all bad.
As the months and years roll along in this post-AI world of business, and as the hype curve wanes, the true productive uses will emerge quickly and relentlessly, and we will edge toward a moment when suddenly the notion of the absence of AI will be all but forgotten.
A bit of history…
In a recent talk on AI, I noted, to mild surprise, that the actual term “artificial intelligence” has been around since 1956. In fact, Alan Turing not only holds the title “father of modern computing” but also contributed to the United States’ ultimate victory during WWII.
A series of rapid developments after Turing’s computer laid the groundwork for what we take for granted today: In the 1970s, research was already underway to have computational systems solve complex problems. In the 1980s, AI was already being used on a limited basis in robotics and computer-aided drafting.
In fact, by the 2000s, we were already devising neural networks capable of deep learning in what, in many cases, were the precursor to today’s large language models. The most famous computer brain of its time, IBM’s “Watson,” even beat Ken Jennings at Jeopardy in 2011.
The last 13 years have simply been a whirlwind of accelerated development with literally no end in sight and tech stars such as Elon Musk and Mark Zuckerberg advancing their own agendas and roadmaps toward an AI-driven future.
Our own advancements
Progress toward robotically driven processes has been a bit slower in the architecture, engineering, and design world. Due to the highly regulated nature of design, the industry is taking a cautious approach and carefully vetting the wide variety of options now on display.
Much like Building Information Modeling was adopted slowly and then quickly, the use of advanced technologies in the built world will likely follow a similar course.
Cautious, slow, then all at once.
At the front end of many projects, we have a robust data collection and modeling tools ecosystem. The proliferation of these tools will greatly impact the surveying and engineering industries by providing newer, better, and more innovative ways to gather existing conditions information where it was inaccurate or non-existent. That goes for construction site monitoring and mapping as well. With AI-driven drones, we have “eyes in the sky.”
Next up, generative design is one of the obvious ways to leverage the ability of AI systems to perform recursive design exercises, leading toward a statistically perfect outcome or panel of options. Many of the leading software manufacturers are publishing or promoting their vision for this (just plug in your favorite software vendor + “AI” over at YouTube, and you’ll see the hype videos).
However, we do not yet have a regulatory awareness of the capabilities advanced AI/ML systems will no doubt provide. Therefore, we’re on rocky footing when we rely solely or too heavily on autonomous design modules. Which is to say, the human attendant is still responsible for what takes physical form, through and through.
Some other common uses include energy optimization in buildings, construction management, and, of course, AI-driven maintenance management that helps make buildings operate better with more excellent reliability.
What does the future hold?
The genie is out of the bottle. We are already seeing significant accelerated adoption of AI and ML tools throughout our industry. This will only continue.
As these tools develop, they will lead our industry to a more in-depth analysis of our projects. This does not necessarily mean a reduction in staff; it will lead us to a different type of staff, such as data analysts.
Work is also being done to educate our lawmakers about these new design systems’ capabilities (and risks). As they better understand these risks and the significant benefits, the delivery systems and the supply chain they belong to will evolve steadily.
Blue chip software companies will continue to develop their core offerings. Still, in most cases, they will include “value-added” capabilities in bundle form, providing them the necessary leverage to raise license costs and improve their revenues.
Much like earlier waves of software development and adoption (CAD, internet, email, web, social), there will be brief moments where breakout firms can enjoy differentiation. However, in an open marketplace, all firms will have access and will adopt, which will continue the leveling cycle of playing fields.
As we lean on our professional associates to work out some of the legal and ethical considerations associated with using AI, we must also choose a path that feels appropriate for our firms and clients. We can all establish that unique value proposition in our markets.
Artificial intelligence poses significant risks to humanity — if abused and misused.
Artificial intelligence poses significant advantages to humanity — if used innovatively and responsibly.
Let those maxims sink in as you evaluate and adopt any type of technology since the boundaries around what we think of as AI will only loosen and become more porous. As always, the value we derive from technology is entirely up to how it is adopted and used.
Let this article serve as a call to action. You must accompany your technology adoption with active and healthy participation with your professional affiliations and associations. They hold the keys to broad, sanctioned usage and adoption and are also part of the pathway to sensible legislation regarding any associated liabilities.
About the Author
Markus Weidner is Pennoni’s chief innovative officer, based in their Philadelphia, PA, offices. He is a nationally recognized director of information technology with strong skills in business applications, infrastructure, collaborative technologies, and the integration of mergers and acquisitions, always ready for the next great growth opportunity.
Markus is a seasoned IT executive with 20 years of hands-on experience in a broad range of areas, including technology infrastructure, ERP implementations, business process and workflow reengineering, document management, project management, and unified communications.
We would love to hear any questions you might have or stories you might share on integrating AI and automation in the AEC industry.
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To your success,
Anthony Fasano, PE, LEED AP
Engineering Management Institute
Author of Engineer Your Own Success