New research from the Futurum Group shows construction companies are closing the workforce capacity gap with a sharp shift toward digital workers powered by agentic AI
IFS had previously found that construction and engineering businesses were losing 41% of their time on manual, repetitive tasks, creating a capacity gap across organisations. Agentic AI agents that autonomously monitor, decide, and execute operational tasks, escalating to humans only when judgement is required, could be key to filling this gap.
Several businesses in the industry, including Kitron Group and KLN Family Brands, are using digital workers to reclaim dozens of hours a week on core procurement and order-to-pay workflows, with several pushing toward fully automated processing with no manual intervention.
The construction workforce capacity gap is becoming increasingly costly
The capacity gap – the widening distance between the work construction businesses need to do and the actual capacity of their teams – is becoming increasingly costly for them to ignore.
A workforce change is also already underway and hitting industrial organisations hardest: experienced engineers and operators are retiring across factories, utilities, and supply chains.
Somya Kapoor, CEO of IFS Loops, explained: “The capacity gap is a high-stakes problem in construction and engineering operations. When a purchase order, a maintenance schedule, or a supplier delivery falls behind because there aren’t enough hours in the day for the worker, the cost shows up as downtime, missed deliveries, or idle equipment.”
Agentic AI agents harmonise the gap between technology and human judgement
Construction companies want to address the capacity gap with new technologies but hesitate to fully trust automation.
The research underscores the need for human-in-the-loop agentic AI deployment models, where digital workers handle high-volume, well-defined tasks while people make judgement calls.
The research focused on the manufacturer Kitron Group, which is rolling out purchase-to-order digital workers across all 13 of its sites by the end of 2026, built directly into the software the business already uses.
This meant that the guardrails and rules the business had already set up were followed, and the existing approvals process stayed intact.
During this rollout, a digital worker surfaced a decade-old part-number error that a manual process had missed for years, showing that digital workers can find and fix data problems as they run, instead of requiring a data cleanup project before deployment.
“Closing the construction and engineering capacity gap takes more than general-purpose AI,” Kapoor stated.
“Digital workers built for the job, integrated into the systems already running the business, are what let teams reclaim capacity instead of just working around the shortfall. Our customers prove that model in production, not pilots.”
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