88% of Contractors Are at Their Lowest Backlog Since Lockdown. The Other 12% Have Never Been Busier.
This week's briefing covers three things that landed in the same fortnight and point in the same direction.First, a closed room in central London. The CTO of DPR Construction, a 14 billion dollar US contractor, sat around a table...
This week's briefing highlights three converging developments shaping the construction industry’s near future, from pricing models and backlog trends to emerging AI capabilities.
Industry Pricing and the Hours Model Challenge
In a closed London meeting, the CTO of DPR Construction joined leading contractors, engineers, investors, and founders to confront a key industry shift. Major clients are demanding supply chains price projects based on outcomes rather than hours, with expectations for prices to decrease annually. Despite this, no clear replacement for the traditional hours model has emerged. Meanwhile, AI pressures are expected to impact back-office functions before on-site operations, complicating efforts to rethink established practices amid busy project schedules.
Backlog Trends Across US Contractors
According to the Associated Builders and Contractors survey, the average backlog for US contractors has dropped to eight months, the lowest since January. This decline spans all regions, sectors, and company sizes. A notable divide exists: 12% of contractors involved in data centre projects maintain a backlog of 11.4 months, while the remaining 88% hold only 7.5 months. This gap increased from 2.5 months in June to 3.9 months in July.
Meanwhile, Fluor’s stock surged 17.4% in one day, reflecting investor confidence in contracts linked to power projects where risk is transferred.
The Impact of Open Weight AI Models
Meta and Nvidia released open weight AI models, significantly reducing the cost of running these systems—from $30 per million tokens in 2023 to fractions of a cent today. Gartner forecasts further cost reductions up to 90% by 2030. This shift threatens companies that rely on third-party AI models, as construction firms with proprietary project data are positioned to gain competitive advantage by training AI on unique internal datasets, beyond relying on external weights or products.
Join the conversation by sharing your thoughts on this week’s questions in the comments of the LinkedIn post.
