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The Real Impact of AI in Construction for Leaders to Tackle Broken Processes and Data Centre Demands

The Real Impact of AI in Construction for Leaders to Tackle Broken Processes and Data Centre Demands



In this special roundtable episode of The ConTech Crew, Jeff Sample is joined by Jonathan Marsh, CEO of SteelToe Consulting and a technology strategist, Nathan Wood, Founder & Chief Enabling Officer At SpectrumAEC, Travis Voss, Director of Innovative Technology and Fabrication at SMACNA and Jacob D’Albora, Director of Digital Building Operations at VIATechnik for a spirited conversation on the convergence of AI and construction. With insights rooted in practical experience, the group digs into what’s hype, what’s real, and what’s starting to deliver value on jobsites and across the back office.

The first half of the episode tackles the evolving conversation around AI - from technical distinctions between LLMs and traditional models, to the construction implications of large data center builds, labor disruption, and the accelerating demand for faster delivery. This isn't just a news recap - it's a temperature check on where the industry actually is with AI.


Key Learnings:

  • AI success depends on clearly understanding indeterminate vs determinate systems.
  • General-purpose AI tools are giving way to custom-trained, domain-specific models.
  • Speed-to-market is now a bigger priority than cost in many projects.
  • Data center buildouts are driving unprecedented infrastructure urgency.
  • AI may help streamline construction processes but only with quality inputs.
  • The labor shortage is shifting from field crews to project managers and assistants.


Timestamps:

[00:00] - Introduction

[04:38] - Jonathan breaks down AI model trends

[06:41] - Determinate vs indeterminate systems

[13:51] - AI’s role in workforce augmentation

[19:02] - Consensus, standardization & AI process help

[23:58] - The problem with over-promising AI

[30:01] - Permitting, tariffs & volatility

[35:11] - Why contractors hesitate to say no


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  • Published on 1 month ago






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