Amelie Barrau, head of regional marketing, EMEA at OpenAsset, discusses how Artificial Intelligence is changing the landscape for construction bidding
The discussion around artificial intelligence and the built environment frequently centres on whether it replaces professional judgement. Spend time with bid teams, however, and a very different story emerges. AI won’t help bid teams win work just by creating a better answer to a question. It’ll help them navigate a procurement environment which has become increasingly tough over the past few years
The market is changing. Viability has slowed development because of increased costs, delayed planning, tougher regulations and limited funding. Since the Grenfell Tower disaster, building safety legislation has significantly raised the bar around the evidence that clients need from their design and construction partners. Sustainability requirements are constantly evolving as Biodiversity Net Gain, whole-life carbon and net zero goals now become embedded in many submissions rather than being standalone elements.
Procurement, meanwhile, is also changing. Last week saw the introduction of new social value requirements in which the weighting of social value in major central government procurements has doubled from 10 to 20 per cent. That will mean even more evidence gathering and tailoring for every single submission. Meanwhile, the government’s drive to boost affordable housing has created clear opportunities for well-positioned practices. The key will be demonstrating capabilities with even greater consistency, speed and accuracy than before.
Construction bid teams need more information
With all that in mind, I have spent the past few months discussing AI with bid leaders and marketing teams across architecture, engineering and construction.
What I found surprising was how little those conversations revolved around writing. Instead, they revolved around finding information.
Most businesses already have a huge amount of knowledge in their possession. Years of successful framework submissions, technical responses, project sheets, CVs, award submissions, and case studies contain all the answers to the questions they are going to be asked in the future. Unfortunately, much of that knowledge is often inaccessible, residing in shared drives, legacy document management systems, folders, individual inboxes, mobile phones, or even people’s memories. And people leave…
It’s a common problem. When I ran marketing in the industry, there was never a week that went by without someone in bids asking whether we had built a Passivhaus scheme, a Net Zero development or a scheme with a specific element that a client wants evidence of. We usually did; the problem was finding the information and getting it to them quickly enough.
Anyone who has dealt with legacy systems will understand the frustration. I used to joke that, once something disappeared into the system, it entered no man’s land. Important emails became difficult to find, project information was fragmented, and bid teams regularly found themselves sending out messages asking colleagues whether anyone knew where a specific case study could be found. Precious time would be wasted looking for information the business already had.
The second common theme emerging from our conversations was trust.
More and more clients are asking whether AI has been used in preparing bids. Many bid team leads are currently unsure of how much to tell and where clients draw the line between using AI as a productivity tool and relying on it to create substantive responses. Most felt comfortable using it to search for information, summarise documents and structure content. Fewer were comfortable allowing it to draft technical responses without substantial review. That is sensible.
The risk isn’t with the technology. The risk is with the assumption that speed is a substitute for judgement. Large language models don’t know whether an accreditation has expired, a project value has changed, legislation has been updated, what a community feels or experiences, or if the selected case study is right for that specific client. And some definitely won’t read through your 50+ documents that form part of the tender. Those decisions still require professional experience and knowledge of the project, the area, and the procurement process.
One bid lead told me that certain admin tasks had gone from hours to minutes and that’s great. However, another told me that the real shift wasn’t about content being written faster; it was about no longer losing hours hunting through old submissions for evidence that already existed. The businesses seeing the biggest gains are the ones treating this as a knowledge-retrieval problem, not just a text-generation one.
This is a problem that construction bid teams are increasingly having to address; needing a tool not just to help you write strong bids, but to make the knowledge you already have findable and reusable for stronger submissions. That’s a more valuable ambition than “AI writes your bid.”
None of this takes away the need for experienced bid teams. It shouldn’t either. Winning work requires judgement, collaboration and understanding what clients and the communities you design for actually want.
But the math has changed. Social value weighting has doubled overnight. Safety evidence has never been more heavily scrutinised. Every submission now has to prove more, to a higher standard, in the same amount of time, and those that can find their own evidence fastest will have a competitive edge. What technology can do is remove the inefficiencies that have quietly been wasting countless hours for years.
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