A recent article from RSM highlighted examples of how Generative Artificial Intelligence (Gen AI) may be implemented in the construction sector, with a particular focus on how its use in the design and planning stages could help to improve margins. For examples of AI and technology already in use today, we can point to many examples, including:

• Balfour Beatty’s development of a Gen AI assistant “that can help with mundane and time-consuming tasks”
• V-Lab Ltd’s £165,000 government grant to support its development of virtual reality training for construction staff
• The rise of decision intelligence platforms which use AI to optimise supply chains, reducing transport and storage costs

It's important to note that, whilst these solutions all offer the promise of improved margins, this is not achieved by simply reducing headcount. Investing in analytics, AI and other data-based solutions acts as an enabler for human experts, rather than a replacement. It allows them to add a creative spark to a design or spend more time on specialised, value-add tasks. It also promotes safer training, rather than risking costly on-site incidents. Lastly, it enables decisions to be taken 24 hours a day, optimised based on previous successes but still overseen with human input. Developing AI capabilities today is about giving more capacity and informed data to allow your experts to make better decisions for your business.

Looking 5-10 years ahead, AI capabilities are only going to increase and it may affect headcount and diversify the roles within the construction workforce. Whilst it may seem obvious that any business not embracing an AI-led future is doomed to become increasingly uncompetitive, the consumer reaction to these changes is yet to be determined. In manufacturing, there are businesses who proudly label their products ‘handmade’, it is highly likely that there will similarly be businesses who advertise themselves as ‘Gen-AI free’. Choosing to use Gen AI, for example, as a replacement for the current architectural process will be a choice.

But for now, whether it’s analytics, automation, AI or other technology solutions, middle market businesses are beginning to set themselves up for digital change. The construction sector is not unique and, although it has in places been slow to embrace change, there is a wealth of data potentially available to be analysed. This includes:

• Analytics from data collected from contractor costs and completion rates
• Predictions of plant breakdowns based on connected sensor data
• Computer vision analysing body-worn cameras and drone camera footage for site safety and quality assurance purposes

But, regardless of whether business decision makers view their data as having value, the government clearly does, with increasing levels of mandatory reporting, especially around ESG. Questions on where materials were sourced, where they were fitted and by whom, and their carbon footprint could be dug out manually from various records, or it could be part of an automated analytics system that allows real-time visibility and reporting. 

AI, Gen AI and even reporting analytics rely on quality, available data. Our interactions with middle market business leaders consistently indicate that, regardless of industry, well over 50% believe their data is currently poor or is not fit for the future. It’s no coincidence that a similar proportion tell us they have inconsistent application of data governance across their businesses – or indeed no data governance framework at all. But a data governance framework should be the cornerstone of any business’ data strategy, creating the environment so that data can be effectively captured, manipulated, stored and used. It also sets the boundaries within which business users know they can utilise data, minimising regulatory and reputational risks.

Not all construction businesses will want, or need, to jump into the deep end of advanced AI modelling. But moving from manual to automated monthly reporting or implementing a Gen AI bot to enhance knowledge visibility across the business are just two examples from many achievable advances that can be made in a business that has good quality, well-governed data. The first step is a mindset change to understand that your data can have value, if treated accordingly.

October’s ICAEW webinar featured specialists from RSM UK’s construction and data analytics team. They discussed the outlook for construction and explored how data and AI may transform business operations.

• Watch the recording