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    AI drywall planning: design and costing implications for UK project teams

    May 12, 2026|

    Reviewed by Joe Ashwell

    AI drywall planning: design and costing implications for UK project teams

    First reported on The Construction Index

    30 Second Briefing

    The University of Wolverhampton has begun a Knowledge Transfer Partnership with Drywall Steel Sections Ltd to develop AI-powered tools for designing and costing light gauge steel framing and drywall systems. Current manual take-off and pricing workflows can take several weeks and are often unrecoverable pre-contract costs, while the planned digital system aims to cut this to a few hours and improve quantity and cost accuracy. For contractors and designers, faster, more reliable steel stud and board layouts could tighten bid margins, reduce abortive design effort and support more standardised detailing.

    Technical Brief

    • Collaboration is between University of Wolverhampton researchers and Drywall Steel Sections’ in‑house LGSF technical team.
    • Company-side KTP lead is Tharinda Rathnapala, LGSF technical manager with prior KTP associate experience.
    • Academic lead Professor David Heesom brings prior AI and digital construction research into a commercial detailing environment.
    • Co-lead Dr Nigel Moore provides additional technical oversight from the university side on modelling and implementation.
    • Managing director Mayank Gupta is sponsoring the change in internal design and pricing processes.

    Our Take

    The collaboration between the University of Wolverhampton and Drywall Steel Sections Ltd positions the UK as one of the more active European hubs in our coverage for university–industry AI applications in construction, which can make it easier for contractors to justify trials on live projects.

    Because this is tagged as both Product and Projects, it suggests the AI tool is being framed not just as research but as something ready for deployment on real UK jobsites, which typically shortens the lag between prototype and specification by main contractors and Tier 1s.

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    Prepared by collating external sources, AI-assisted tools, and Geomechanics.io’s proprietary mining database, then reviewed for technical accuracy & edited by our geotechnical team.

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