Artificial Intelligence is lagging in construction?

Artificial Intelligence is lagging in construction?

Artificial Intelligence is the buzz word today.  What Artificial Intelligence really means is machine-based thinking which is programmed to perform simple tasks.  And that’s a good thing, as the applications are numerous.  We are replacing human intervention with AI for routine tasks which are downright tedious for mortals like us.


But what is the impact of Artificial Intelligence on the AEC industry?

However, a shift is coming. Stakeholders across the project lifecycle—including contractors, operators, owners, and service providers—can no longer afford to conceive of AI as technology that’s pertinent only to other industries

Adoption of AI solutions is quite low in the E & C particularly compared to other industries. The reason for that is because the industry remains severely under digitized. According to McKinsey, AIs proliferation in the E&C sector is expected to be modest. Despite the proven high return on investment (ROI) and widespread management interest in AI solutions , few E&C firms or owners currently have the capabilities including the personnel, processes and tools to implement them.

However, a shift is coming. Stakeholders across the project lifecycle—including contractors, operators, owners, and service providers—can no longer afford to conceive of AI as technology that’s pertinent only to other industries

AI use cases in construction are relatively nascent, though some startups are gaining market traction and using AI focused approaches. There are few use cases that construction companies can evaluate-

The current state of AI on engineering and construction


  • Project schedule optimizers can consider millions of alternatives for project delivery and continuously enhance overall project planning.
  • Image recognition and classification can assess video data collected on work sites to identify unsafe worker behavior and aggregate this data to inform future training and education priorities.
  • Enhanced analytics platforms can collect and analyze data from sensors to understand signals and patterns to deploy real-time solutions, cut costs, prioritize preventative maintenance, and prevent unplanned downtime.
  • Firms can use deep-learning techniques to enhance quality control. Neural networks can, for example, assess drone-collected images to compare construction defects against existing drawings. These networks are also capable of helping owners and firms alike understand the likelihood that a contractor or subcontractor will file a claim, enabling owners and firms to proactively allocate contingencies and deploy targeted mitigation plans.
  • E&C stakeholders can use neural networks, using drone-generated images and laser generated data capturing project progress, to teach an AI how to create 3-D “twin models” to match BIM-generated models. These applications would dramatically reduce decision-making cycles in a construction project from a monthly basis to a daily basis— through full automation of the project scheduling and budgeting update on the combination of BIM, AI, drone, and laser capabilities

Of course, any AI algorithm is based on learning from the past. This means that AI needs a certain critical mass of data to deliver on its promise so scale will matter; as such, firms will need a significant amount of data (in this case projects) to train an AI algorithm. Therefore, the largest companies are likely to benefit more, particularly in the short term.


                     

Eliminating tunnel vision 

Everyone has a vision. 

AI eliminates tunnel vision by presenting a range of possible scenarios, based on data and falling within project budgets and timelines. What remains to be done in terms of successful integration of AI into the AEC industry is for data to be diligently collected and collated, so that AI has reliable data to work with. Data stewardship in the industry will determine the impact of AI on the AEC industry, but when that part of puzzle is in place, the applications are almost endless.  That means saved time, money and greater efficiencies.


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References – https://www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/artificial-intelligence-construction-technologys-next-frontier

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