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Construction and AI



Construction is one of the many industries undergoing a fundamental change in process optimization, with the advent of AI. Every element of the approach to delivering a finished built space is poised to gain tremendously, by harnessing the power of intelligent computing in the service of better buildings and cities. While some aspects of construction, such as the design process and fabrication, are more apparent opportunities to the layperson, almost every element in project management stands to benefit. Construction has traditionally been relatively cautious in adopting new technology, but while there is currently a lag, possibilities for gains exist across multiple processes, from schedule and subcontractor management to site monitoring and safety.


The engineering and construction (E&C) industry represents a ubiquitous global presence and colossal cumulative investment of resources, capital, and manpower. The sector is currently pegged at an astronomical $10 trillion a year (1). However, despite its huge investment in mechanization, the industry remains far short of its potential in digital technologies. A recent McKinsey report has found that the construction industry has the potential to gain $1.6 trillion in productivity if it incorporates appropriate digital transformation (2). The potential for intervention exists from the earliest design stages and processes undertaken during construction to the incorporation of digital technology in the ongoing maintenance of built spaces. AI-enabled algorithms have the potential to create a tremendous bottom-line impact in costs, optimal scheduling and safety issues.

The emerging picture in untapped opportunities


The E&C industry can no longer ignore the solutions that AI can enable. With newer entrants and start-ups favoring the technology to create disruptive impact, traditional high capital players are also starting to notice the competitive advantages. However, despite the traction that the few early adopters have gained, instances of deployment remain relatively limited. Some of the initial success of the disruptors has been built around project schedule optimization, monitoring of site video for safety using image recognition and enhanced analytics relating to capital control and proactive maintenance. The possibilities for further implementation are even more impressive and include:


  • Generative Design: Mimicking the evolutionary and adaptive processes in nature, generative design is a particularly useful deployment of AI that allows machine intelligence to be recruited for rapid and flawless iteration of ideas. It has the potential to consider options and use design goals and comparative analysis to identify opportunities. 

  • Overall Project Planning: The reinforcement learning approach, that AI and machine learning make possible, result in a far more agile project planning process. It becomes possible to include far more permutations than humans can incorporate while retaining the capacity to respond to changes in goals, schedule, and resources. 

  • Increased productivity: Self-driving, intelligent machines are an inevitable evolution of the legacy mechanization within the E&C industry. Apart from sheer speed and accuracy, such machines have the advantage of being able to be deployed in ways that would be too dangerous for human workforces. 

  • Offsite Prefab construction: It is possible to reduce construction costs and impact schedules radically, using offsite fabrication of elements which are then put together at the project site. For instance, AI-controlled machines, both at the prefab end and the project premises can be easily coordinated to render the basic structural essentials using a modular approach. Human workforces can then add details and infrastructure such as HVAC, plumbing and electrical systems. 

  • Risk Mitigation: With multiple workforce teams involved – several of which are subcontracted – risk mitigation can be a challenge in the construction industry. AI can enable powerful ongoing analysis, allowing priorities to be assigned to tasks as they become a risk. Real-time data gathered through IoT deployments can further reduce risk through anticipatory intervention. 

  • Leveraging data and breaking silos: The E&C industry consists of a very wide array of processes, teams and third-party inputs. Integrating and optimizing such a diverse set of variables introduces very significant advantages. As IoT technologies permeate the industry more and more, the possibilities to achieve this integration through an appropriate suite of AI algorithms are on the rise every day.

The sheer possibilities for capital, resource and process optimization that AI can bring to the construction industry constitutes an irresistible argument. However, the benefits go beyond mere process control. The ability of AI to consider a very significantly higher number of solutions for an issue can spark a new age of innovation in an industry that has hitherto relied on the proven credibility of established practices and procedures. AI has the potential to not just enhance these legacy methodologies, it can completely transform the very nature of the solutions and designs that the industry adopts for its internal processes and the structures it delivers to its customers.


Conclusion


The construction industry brings together a diverse range of stakeholders, high-pressure stakes and very specific and targeted outcomes. While mechanization has increased efficiencies and productivity in the industry for several decades now, AI holds the key to truly dramatic recruitment of that machinery.


1 Anastasios Koutsogiannis. “Artificial Intelligence: The Future of Construction.” GenieBelt, 7 Mar. 2019, geniebelt.com/blog/artificial-intelligence-the-future-of-construction.

2 “Artificial Intelligence: Construction Technology’s Next Frontier.” McKinsey & Company, Apr. 2018, www.mckinsey.com/industries/capital-projects-and-infrastructure/our-insights/artificial-intelligence-construction-technologys-next-frontier.

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