By VIVIEN PEADEN

The commercial construction industry is undergoing a seismic shift as artificial intelligence tools rapidly reshape how projects are planned, managed and delivered.

Advancements in AI and machine learning – including those in generative AI, robotics augmented reality and virtual reality – are streamlining every stage of the engineering and construction processes.

According to a recent Autodesk survey, the AI in construction market is expected to grow to $24.3 billion by 2030.

AI should be used by contractors, engineers and design professionals to augment their roles in the planning, design and building phases – not to replace their own professional judgment and expertise. The American Society of Civil Engineers cautions that “AI cannot serve as a replacement for the professional judgment of a licensed professional engineer” and that such technology is no substitute for an engineer’s training and experience.

The message to civil engineers and the greater construction industry is clear: Engineers will be held accountable for the data upon which they base their decisions, recommendations and representations, regardless of whether such data was computer-generated. An engineer – not the AI application used by the engineer – will ultimately be responsible for violating any applicable standard of care.

According to the National Society of Professional Engineers, engineers using AI are held to the same professional licensure standards as traditional engineers for purposes of public safety, health and welfare. Similarly, the National Council of Architectural Registration Boards has stated that “any proposed regulation that addresses AI usage in practice must ensure the licensed practitioner remains in responsible control and continues to be accountable for all technical submissions under their seal.” In other words, AI tools cannot stand in for an architect’s or professional engineer’s stamp on drawings.

AI has significantly changed how the construction sector approaches project planning and field operations. Integrating AI into commercial construction workflows and processes means that companies are handling unprecedented volumes of data that boost forecasting, site safety and productivity.

According to an MIT survey, while only 40 percent of companies have officially adopted learning language mjodel subscriptions, more than 90 percent of workers report regular use of personal AI tools for work. While employees’ unauthorized use of public AI tools can drive productivity, such use can simultaneously expose an organization’s proprietary information (including pricing information and sensitive personal data), waive privilege and result in breaches of contractual obligations.

Many non-enterprise AI tools are becoming generally accessible through web browsers and mobile app add-ons to existing platforms. As a result, most organizations lack visibility to conduct a meaningful audit or assessment of potential risks posed by widespread internal adoption of Shadow AI.

To mitigate the hidden threat of Shadow AI, organizations must stay vigilant by implementing AI-driven governance, monitoring and protection mechanisms. One key step is to establish and enforce clear policies governing employees’ and contractors’ access to non-enterprise AI models and the permitted and prohibited uses of company information input into any third-party AI tools. Another effective step is to build or deploy corporate firewalls or gateways that automatically block sensitive data submission and scan activities according to company security policies.

AI is a tool to bolster and augment construction and engineering processes; however, it is not a substitute for professional judgment in the planning, designing and building phases of construction projects.

Organizations should focus on responsible governance of their enterprise AI ecosystem through a cross-functional AI risk committee involving IT, cybersecurity, finance, marketing and legal departments.