This year, Building asked firms for specific examples of AI and machine learning solutions that they have used, and what they learnt. Carl Brown reports
Artificial intelligence dominated the media at the tail end of 2022 and throughout 2023, following the emergence of mainstream generative AI tools based on large language models such as ChatGPT and Google Bard/Gemini.
Our Top 150 Consultants survey last year asked respondents for the first time about AI and machine learning, and we found the industry placing a large amount of importance on them.
>> Read more: Top 150 Consultants 2024: Where do you stand on hybrid working?
And this year the interest in AI and machine learning has not gone away – in fact, our survey shows consultants are taking it even more seriously.
We again asked the consultants how important they think AI and machine learning will be to the transformation of their business over the next 10 years.
How important do you think AI and machine learning will be to the transformation of your business over the next 10 years?
This time around 88% of the 159 businesses to respond said they consider AI and machine learning to be very or extremely important. This is up from 75% when we asked the same question 12 months ago.
The percentage saying they consider AI and machine learning to be extremely important has jumped from 28% to 40% year-on-year.
How important do you think AI and machine learning will be to the transformation of your business over the next 10 years?
It is clear that AI and machine learning are increasingly being seen as important for businesses’ futures.
In 2023 we asked consultants to describe the business areas in which they thought AI and machine learning would have most impact. Several areas or tasks were mentioned by multiple respondents, including design, bid writing/bidding, automation of tasks/efficiency, surveying and data gathering/analysis.
This year we decided to shift the focus towards specific applications of AI and machine learning in the industry.
Simon Rawlinson, head of strategic research and insight at Arcadis, says: “I’d be interested in the extent to which the organisations who have responded to this survey have actually invested in things like Copilot with Microsoft – so whether they are actually paying for that service as part of a licence or whether they are just basically using ChatGPT, which as we know is limited… or whether they’ve got their own in-house chat applications.
“There is a sense that people think AI is more important, but what are they actually doing to bring it to fruition?”
So, what are firms actually doing? Below are snippets from some of the responses to our survey.
Have you implemented an AI solution/tool into your business in the last 12 months? If yes, what was it and do you have results or impacts from it you can share?
Turner & Townsend: “In addition to trialling commercially available AI for general productivity, we are piloting OpenAI and Google Gemini solutions within our cloud applications to improve the quality of our core deliverables.
“Results so far are promising but appear limited by the current capability of AI. Collaborating with clients and partners, we’ve introduced AI tools like Buildots, Nodes & Links, and BuildPrompt. Buildots monitors site progress, Nodes & Links analyses schedules for efficiencies, and BuildPrompt discreetly prompts data for client queries.”
Arup: “We have already deployed multiple AI systems as a way of augmenting human intelligence, to enhance our design, engineering and consulting offers to our clients, with a particular focus on achieving sustainability outcomes. One example of this is Uheat, a digital solution designed to help urban planners and city authorities to bring down the temperature – also known as the urban heat island effect. By using a combination of satellite imagery and AI trained on open-source climate data, we are now able to analyse huge areas of cities and the particular buildings, structures and materials that are causing temperatures to rise.
Mace: “We currently use specialised AI tools across a number of very specific use cases. In the last 12 months Mace has undertaken trials of a number of more general-purpose generative AI tools across a variety of office productivity tasks. We have yet to progress to widespread deployment of generative AI technology.”
JLL: “We have implemented our own secure AI tool for internal use. JLL GPT is an AI assistant. Since its launch, JLL GPT has offered numerous benefits including enhanced efficiency, improved decision-making capabilities and simplified data analysis. By automating routine tasks, providing real-time insights, and leveraging advanced natural language processing, JLL GPT has empowered users to streamline workflows, save time and make more informed business decisions.”
Todd Architects: “MS Copilot – helped with responding to development of documents and reports and input on submissions. Revit Suite – using software to allow parametric design, our Revit group have been exploring the ability to establish for initial feasibility studies such as capacity studies on residential schemes.”
Systra: “We have an internal large language model tool that allows staff to access the benefits of a ChatGPT type solution but within a secure organisation environment.
“This is increasingly being used to help with reviewing documentation, initial understanding of opportunities, basic background research in new subject areas.
“We also have an AI-powered automated tool for checking standard design documents. We have an AI supported knowledge-sharing internal tool. We are in development of a number of other AI applications across the business and we have developed a number of machine learning applications for clients.”
Magnitude Quantity Surveyors: “We have been building a proprietary software for construction cost benchmarking, which following launch will have an integrated carbon calculator.
“We have utilised AI to assist with coding, which has significantly reduced the cost of external consultancy assistance.”
Hydrock Group: “We’re in the process of implementing an AI tool, which is currently being trialled across our business, that reviews our invoices and reflects the likelihood of those invoices being paid on time.”
Stantec: “We are testing Microsoft’s Copilot AI assistant, allocating licences across our global organisation – the first phase aims to quantify productivity gains across six of the most used applications. The second phase assigned users to focus groups to comment on their learnings, most practical uses, accuracy and perception of its value. Results indicate that Copilot is resoundingly useful. The most frequent uses were generating Word content, summarising Teams meetings and searching emails, meetings and chats using Microsoft365.”
Aecom: “We are building an AI knowledge platform to support our teams, starting with AI-driven software to significantly speed up bid information-gathering, so that experience and expertise globally can be drawn together in seconds. This is now being expanded into enterprise resource planning and customer relationship management.”
Hoare Lea: “We’re using an open-source large language model running off-grid within our organisation with secure access to our design data and internal guidance and standards. We’re seeing some very encouraging early results, saving engineering teams hours of work to manually find answers. We’re also getting some exciting results in getting the LLM to directly query our own engineering data platform to provide predictive support in early-stage design.”
“We’ve applied machine learning to uncover insights from large public sector datasets to identify work-winning opportunities. We have developed a generative AI chatbot for client biodiversity enquiries and are prototyping a generative AI chatbot for employees to better access our knowledge base.”
Barker Associates: “We have implemented Synthesia – an AI solution to create video content for internal and external communications.”
Baily Garner: “Yes, Autogen [an open-source programming framework for building LLM applications] This does positively impact efficiency and productivity, however requires trained, experienced and skilled operatives to bespoke and be of use, otherwise it can be misleading.”
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