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Artificial intelligence (AI) and machine learning (ML) are becoming increasingly popular in North America, and it’s only a matter of time until they’re implemented on building sites.
Despite projections of significant job losses, AI will not be able to completely replace the human workforce. Instead, it will change the construction industry’s business models, reducing costly errors, reducing jobsite injuries, and increasing the efficiency of construction operations.
Construction executives should focus their investments on areas where AI may have the greatest influence on their company’s specific demands. Early adopters will shape the industry’s future and benefit in both the short and long term.
The North America AI in Construction Market accounted for $XX Billion in 2021 and is anticipated to reach $XX Billion by 2026, registering a CAGR of XX% from 2022 to 2027.
Zurich North America has implemented Chisel AI’s Submission Intake and Policy Check solutions to automate core Construction underwriting and placement processes, ensure policy quality, and reduce the costs of policy rework and reissuance, according to Chisel AI, a technology provider for the global insurance industry.
The construction industry is now using Chisel AI Policy Review to check and validate policies against binders to discover any errors or omissions, save policy issuance costs, and maintain Zurich’s gold standard for contract quality and certainty.
Urbint, the only AI-powered field risk mitigation platform for critical infrastructure operators, has announced the release of Urbint Lens for Worker Safety, a new predictive artificial intelligence (AI) technology that identifies safety threats to field workers, allowing supervisors to avoid serious injuries and fatalities.
Construction-related serious injuries and fatalities have not decreased. This is due to the fact that many hazards to worker safety, such as electric current and slip hazards, are either invisible or readily disregarded.
Urbint Lens for Worker Safety employs machine learning to identify hidden safety concerns ahead of time, allowing managers to assign and conduct targeted interventions before an event happens.