Over the past five years, a lot has changed in the AEC industry’s view on risk. We’ve seen examples from being risk-averse with strict processes and little room for trying untested solutions to leaning further toward an innovative approach and mindset.
Though the mindset change is underway, risk assessments and adversity to change often still mean a lack of adopting new technology.
AI is a great example of that. While it’s becoming clear AI can be a useful tool to support project efficiencies and data-driven decisions, its potential for the AEC space lies in addressing complex challenges, streamlining automation and optimising processes, but the adoption remains low. But the crux of this change goes further back than the next leading technology and began with a shift in the way the industry views data. What was once seen as numbers and stored information now has value for making decisions.
Platforms like Autodesk Construction Cloud (ACC) are helping change the way people in the industry think about digital tools, by essentially making them more comfortable in using their own data to guide decision-making. In the past, data in the industry was mostly viewed as a way to plan resources, manage budgets and improve quality control. It helped companies make smarter decisions by giving a clear picture of labour rates and material costs.
But lately, some are finding new ways to improve project outcomes and reduce costs in real time. The pandemic sped up this change, disrupting supply chains with limited access to physical job sites, and in turn, forcing construction companies to rely on advanced technology. What started as a requirement, later revealed the benefits of collaboration and managing data efficiently.
While the environment made companies more cautious about risk, it showed them how digital tools could improve how they work together. With this clear change in how data is seen, rather than a hindrance, companies have become more willing to try new technologies that offer real benefits.
This has been seen in the industry’s adoption of trialling energy-efficient design solutions and supply chain processes, where we know the aim is to predict material shortages or delays or other, anything that would have a cost. Right now, AI is being tested in different areas, one being predictive data to help improve project decisions.
These early tests are crucial for figuring out how to turn data into actionable insights to support various projects. We have seen this in the UK and locally in Australia with all the recent infrastructure works around the country.
Whilst the biggest barrier to adopting new technology is resistance to change is still very prevalent across construction, with many being hesitant to change old ways of working, the platform is now there to continue further adoption.
Looking at AI as an example, it’s a technology that brings a lot of hesitation and uncertainty for almost any industry. AI has a lot of potential to change the AEC industry, but its adoption is moving slowly across Australia.
While the technology could offer streamlined improvements, like cost savings, better efficiency, and reduced risks, there’s a concern that this technology taking jobs, overhauling ways of working and changing entire industries. But, these same hesitations are felt when it comes to any new technology.
To see a new technology succeed, companies need to introduce it gradually and make sure it initially fits into existing processes and gradually replaces or replicates these processes, so the same applies when it comes to AI.
The way to successfully apply any new technology is through gradual change, without changing all systems at once. Choosing the right software and breaking down the process into test and trial stages is crucial to working alongside or improving existing operations. Carefully managing this change will be key to helping the industry continue to grow and improve.
With the adoption of AI, the industry will most likely start to see risks managed in advance, as well as the automation of routine tasks, which will give teams more time to focus on important decisions and higher-value work.
Looking ahead, AI could also help to make procurement more efficient and keep projects on track, using BIM to provide data as it happens to automate tasks and improve accuracy.
For AI to be widely accepted, it needs to prove it works in real-world construction projects, companies won’t use it on a large scale unless it shows tangible results that solve problems.
It’s important for businesses to understand how technology can save them money and improve efficiencies by remaining open to looking at new processes.
In the end, there are many pathways AI could go, but it’s set to be a fun ride.
