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report from McKinsey & Company asserts that the construction and engineering industry is behind the curve in implementing artificial intelligence solutions, and that AI proliferation will be modest in the immediate future because relatively few firms have the personnel, processes and tools to manage it.

The report compared the buildings materials and construction industry to 12 other industries, 10 of which are further along in AI adoption and all of which are projected to increase spending on AI at faster pace during the next three years. It also details how engineering and construction firms potentially can apply AI solutions from the retail, transportation, health care and pharmaceutical sectors.

For example, AI could be used to recommend various designs and finishes, compare drone-collected images of defects to existing drawings, gauge the lump-sum price discounts clients may be willing to pay for a project and perform a sentiment analysis on a firm’s market perception. On the workforce front, AI can segment employees based on the likelihood of attrition and develop targeted plans to retain them. Similar tailoring can be done on the recruitment side to attract the right people and identify talent pain points.

Looking ahead, McKinsey & Company suggests engineering and construction companies pinpoint which AI-powered use cases can have the most impact in the short term and funnel investments toward solutions that will be easiest to implement given the firm’s level of digital maturity. On that note, businesses with a strong track record of digitization (e.g., cloud infrastructure and advanced analytics) are 50 percent more likely to generate profit from using AI. Another important piece of the puzzle is hiring people from other industries who have a background in AI, as well as reskilling existing staff to comprehend machine learning concepts and algorithms.

Joanna Masterson. Reprinted from ConstructionExec.com, July 9, 2018, a publication of Associated Builders and Contractors. Copyright 2018. All rights reserved. 

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