As one of the least digitised sectors, it’s hardly surprising that construction scores poorly on productivity. Artificial intelligence has huge potential to transform our industry at every stage of the process
The concept of artificial intelligence (AI) and the related theme of machine learning are nothing new. The great mathematician and code breaker, Alan Turing, was theorising in this subject area during the 1930s.
However, the theory is now mainstream reality, and its application to the construction industry could be more disruptive than many of the elements of digitalisation that are already impacting on our working processes. We consider many of the elements now in place to be revolutionary, but we are just scratching the surface: AI-enabled platforms may leapfrog much of what we are working with.
The UK construction industry contributes around 7% to GDP and employs more than 2 million people throughout the country. As an industry, its societal and economic impact is extremely significant. Full-scale technological disruption in this sector would be far-reaching and irreversible, affecting more than 180,000 companies through the myriad supply chains, contractors and consultants involved.
Research […] shows that the application of artificial intelligence could drive up productivity levels in all industries by 30%
Management consultant McKinsey has recently reported that construction is one of the least digitalised industrial sectors in the world, and this is reflected in its ongoing failure to improve productivity relative to other industries. It is no surprise, then, that out of the 50 smartest companies in 2017, ranked by MIT, not one of them is a construction company.
The UK’s prognosis for a shrinking traditionally skilled construction workforce means that the “push” drivers for change from within industry are now growing. The “pull” of technology has never been greater but still faces resistance.
Research undertaken by Accenture shows that the application of artificial intelligence could drive up productivity levels in all industries by 30% by the year 2035. Fundamentally, AI is a technology that outsources thinking, allowing us to do much more as humans, more efficiently.
While this image may seem some way off from your typical mainstream construction project, I would suggest that early innovators and disruptors are already working on technologies that have mass roll-out potential at every level of our industry, from the design process through to the construction workface.
The pursuit of higher levels of adoption of BIM, in conjunction with traditional fragmented procurement and an analogue on-site construction process, has been problematic. Why are we surprised, when the basic workflow, common data protocols and behavioural alignment are not conducive to unleashing the real power of digitisation? In his Autodesk University lecture, Bill Allen of EvolveLAB suggests that “the future of BIM is not BIM”, and I would have to agree.
It will join the dots in a way that drives mass customisation – not mass standardisation – and engages everyone, including SMEs
The use of generative design and solution optimisation will fundamentally alter how we work as an industry. It will alter the role of planners, designers, surveyors, suppliers and constructors. Combined with smart embedded technology, it will also fundamentally change asset performance management.
It will do this, when combined with digitally enabled premanufacturing, fabrication and on-site assembly, in a way that bypasses all the traditional workflow barriers currently being experienced in piecemeal digitisation of our industry. It will join the dots in a way that drives mass customisation – not mass standardisation – and engages everyone, including SMEs, through simple and accessible digital tools and worker augmentation.
The most important initiator of change is how construction is fundamentally commissioned. Some disruptors are fully vertically integrated and will be masters of their own destiny. Other clients will need assistance through better codification of how specific assets can be designed and constructed from an inter-operable “kit of parts” that is supply-chain aligned.
This still allows for architectural individuality and appropriate differentiation in order to produce high-quality, contextual buildings, but they will all have a common backbone. AI can and should play a key part in this process and may involve open-sourcing the asset-specific AI technology that releases the genie from the bottle when it comes to digital configuration and procurement.
This is the basis of delivery platform thinking, a concept that is further outlined in Bryden Wood’s recent report, Delivery Platforms for Government Assets: Creating a marketplace for manufactured spaces. I am currently investigating ways in which this can be implemented at scale in the homebuilding sector. Combined with process, product assurance and the requisite financial and valuation sector buy-in, this disruption could be truly transformative. Watch this space.
Updated: 31 October