With talk surrounding artificial intelligence (AI) steadily turning to the practical “use case” some new research exposes what may be a divide on the pace, nature and character of the technology’s integration into the design, construction and skilled trade services sectors.
A recent study by Atanzo AI, a Salt Lake City-based AI platform for skilled trades and inspection services, shows strong confidence in and support for AI among workers as a powerful information tool in the field.
But research from the ACEC Research Institute, affiliated with Washington, D.C.-based American Council of Engineering Companies, finds some caution and wariness mixed in with real excitement about AI’s long-term prospects in the engineering world.
AI, it suggests, needs to be mindfully integrated into the soul of an engineering business, paying close attention to the weighting of opportunity and risk, not as just another layer of IT.
The two takes come at the AI question from slightly different angles and might not represent a stark divergence in thought. But they’re at least more evidence that AI thought is maturing and that AI is being evaluated through different prisms in a broad industry sector that could be ripe for ultimately seizing its benefits.
The recent Atanzo research finds that most of the 1,000 skilled trades workers it surveyed in the United States and Europe see AI as something that could help solve a chronic problem: costly mistakes that require callbacks and rework.
In a news release on the findings, Atanzo says nearly half of those polled said they at least sometimes must return to a job site to correct mistakes that could have been avoided with better real-time information. That time-consuming and costly scenario is one that many said they hoped AI could help solve by delivering key information quickly and reliably, potentially eliminating the need to stop work to consult others or conduct time-consuming database searches.
Overall, almost three-quarters of those surveyed agreed that an AI-guided task app would help them reduce the time needed to find essential information. More broadly, two-thirds believe that AI would help them complete job tasks more effectively, resulting in improved productivity and a reduced chance of callbacks and rework.
The Atanzo report based on the research homes in on the problems caused by on-the-job mistakes. It cites a statistic showing construction rework averages 5% of total project cost, amounting to some $30 billion annually, and a typical single HVAC project callback costs $650.
Those costs could grow, the report says, as the construction labor availability challenge grows alongside the steady exit of seasoned and knowledgeable workers and the entrance of minimally trained and less experienced replacements.
Companies in the construction and skilled trade services sectors have made strides in equipping workers with digital tools that can help reduce mistakes, and more workers are utilizing rudimentary off-the-shelf AI tools like Chat GPT, the report says, but “most workplaces sit in a digitally-established-but-not-AI-central middle rather than at the leading edge.”
Meanwhile, more engineering firms are starting to integrate AI into their processes, ACEC says, but the applications are multi-dimensional, complex and consequential, in ways that may eclipse those addressed in the Atanzo research.
The ACEC report, based on distilled published research on the topic and interviews with 21 leading voices in the engineering and broadly adjacent communities, focuses on the multiple game-changing risks AI presents to the industry, concluding that “successful AI adoption will not be determined by which firms deploy the most advanced technologies or automate the greatest number of tasks,” but instead by how well organizations align its deployment with foundational industry values and unwavering commitment to “technical excellence, sound judgment, responsible governance, ethical conduct, and an unwavering commitment to protecting the public.”
In “Leading Through Risk: The Enterprise Framework for Engineering Firm Leaders,” ACEC frames the challenge the industry faces in how it approaches AI integration. The emphasis is on risk – from failing to deploy it to failing to do so carefully and thoughtfully – partly because the technology is powerful, remains in its early developmental stages and can be deployed under competitive pressures that can sidestep due diligence.
“Artificial intelligence,” the report reads, “is transforming engineering practice at an unprecedented pace. While much of the current discussion focuses on technological capability, this report examines a different question: What new risks does AI create for engineering firms, and how can those risks be managed responsibly?”
The answer that surfaces, ACEC says, is strong governance, a rock-solid commitment by firms to stay true to the principles that have guided the profession and allow AI to flower only in firm support and enhancement of time-tested processes and procedures.
AI, it says, has the potential to vastly improve the industry’s work product and the fortunes of its members and clients, but it also carries the power to pull the industry away from its moorings.
ACEC concludes: “Artificial intelligence does not change the engineer’s fundamental responsibility to protect the health, safety, and welfare of the public. It does not diminish the importance of professional judgment, technical competence, ethical decision-making, or accountability. If anything, the interviews suggest that these responsibilities become even more important as AI assumes a greater role in engineering practice. Technology may accelerate analysis and improve efficiency, but responsibility remains with people.”
