CIVALGO

AI: AN ANTIDOTE TO THE CHRONIC PRODUCTIVITY PROBLEM KILLING PROFITS IN THE CONSTRUCTION SECTOR

The digital transformation of the construction world is underway. This revolution has been a major shift for this industry, which represented 13% of the world’s GDP or $10 trillion in 2018 , but which also lags considerably behind technologically. The low productivity of the sector is also problematic. It has been hovering around 1% for two decades, well below the global economy average (2.8%)2.

But the tide is turning. On the connected jobsite front, cloud computing is helping monitor project progress and performance and enables effective collaboration between teams. Visual recognition by drones and autonomous robots, heavy equipment telematics, motion sensors, the future of the construction worksite belongs to big data, and the sophisticated analytical approaches that stem from it. In this context, artificial intelligence is called upon to play an important role in fixing the productivity problem of construction.

 

Several processes—from bid estimation to execution—can be optimized with AI. With this augmented skillset, managers are able to increase speed of execution and decision, reduce errors and rework, driving substantial productivity gains for the project. The AI engine uses analysis, modeling and predictive capacities to anticipate results (planning, scheduling, material management) and understand the causes of problems that could influence the smooth running of operations or impact budgets and schedules.

By applying smart predictive scheduling, AI platforms such as Civalgo improve decision making by helping planners, schedulers and dispatchers to determine the most appropriate time for a task and best combination of teams and equipment—anticipating bottlenecks and avoiding costly downtime.

Duration, material quantities, context are all coefficients of a task considered to allow the new AI systems to learn from each execution it tracks, making it possible to estimate costs and resources required to complete similar projects in the future.

AI project assistance speeds up pre-fabrication, delivers a better return on resources, and subsequently, makes the construction organization more profitable and competitive.

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