Industrial firms are increasingly turning to agentic digital workers as they confront a widening shortage of available capacity, according to research commissioned by IFS and carried out by The Futurum Group.
The study found that industrial employees spend 41% of their time on manual, repetitive work, a burden that is squeezing productivity across factories, utilities and supply chains. As experienced engineers and operators retire, the gap between what organisations need to do...
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IFS says the answer is not full automation, but a human-in-the-loop model in which AI agents take on routine, high-volume tasks while people retain oversight on decisions that require judgement. The company describes these systems as digital workers capable of monitoring, deciding and executing operational processes autonomously, with escalation to humans where necessary.
According to Futurum’s research, 66% of enterprises are likely or very likely to invest in agentic digital workers within the next 12 months. That suggests the technology is moving rapidly from experiment to operational tool, even as many industrial firms remain cautious about handing over too much control.
IFS says its Loops Agentic Platform is built to address that caution by embedding digital workers into existing business systems and preserving approval steps. The company claims the platform can automate 60% of agentic transactions end to end, while the remaining 40% are left for human review and validation.
Several customers are already using the approach in production. Kitron Group and KLN Family Brands are said to be using digital workers to reclaim hours each week in procurement and order-to-pay workflows, with some processes moving towards full automation without manual intervention.
Kitron Group is rolling out purchase-to-order digital workers across all 13 of its sites by the end of 2026. The company says the tools were built into software it already used, allowing existing rules and approval processes to remain in place. During the deployment, a digital worker reportedly uncovered a decade-old part-number error that a manual process had missed for years, highlighting the potential for these systems to identify data issues as they work rather than after a separate clean-up exercise.
Somya Kapoor, chief executive of IFS Loops, said the capacity gap is a high-stakes issue in industrial operations. “The capacity gap is a high-stakes problem in industrial 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. Closing it takes more than general-purpose AI. 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.”
The pace of adoption appears to vary by sector, but speed is clearly a factor. Ependion brought its Supply Order Manager digital worker live across the company in a 10-week phased rollout, while IFS says Kitron is on course to have all 13 sites live in less than seven months.
The backdrop is a broader debate about whether companies have the verification mechanisms needed to move advanced AI from demonstration to daily operations. A separate qualitative study published on arXiv found that while several firms are experimenting with more advanced AI systems, only one of 12 companies studied had reached multi-agent orchestration in production, with human review still serving as the main trusted safeguard. That finding echoes the industrial caution reflected in the IFS research.
The message from both studies is broadly the same: industrial firms are keen to improve throughput, but they are not yet ready to abandon human oversight. For now, the most compelling use case for AI in heavy industry appears to be not replacing workers, but extending their reach.
Source: Noah Wire Services



