An enterprise business survey shows that operational workers are driving real-world AI implementation and delivering tangible, commercial value, but their bosses in the C-suite are lagging behind, according to “industrial AI” software vendor IFS.
The research reveals a “significant divide” between frontline execution and C-suite strategy. Factory floor teams are pushing ahead as they know the operational problems that need to be solved, recognizing that the answers already lie in their institutional knowledge and operational data. But their progress is being slowed because formal AI governance frameworks and data access structures are not keeping pace with gains on the factory floor.
Those conclusions come from the IFS Industrial Index 2026, which surveyed 2,275 executive leaders and frontline workers aged 18–65 across 14 countries: Australia, Denmark, Finland, Germany, Japan, the Netherlands, New Zealand, Norway, Saudi Arabia, Sweden, the UAE, the UK and the US. Respondents were drawn from organizations with more than 500 employees and annual revenue exceeding $250 million, across the following industries: manufacturing, aerospace & defense, energy & utilities, construction & engineering, transportation, and telecoms.
IFS says that when frontline teams – such as engineers, plant managers, service leads, and logistics managers – connect their domain expertise and operational data with Industrial AI, the business impact is immediate. Rapid adoption on the floor is delivering direct commercial returns in savings across key operational areas, despite solutions not currently being used to the fullest. Over 90% of global organizations report significant gains in reliability and performance, as measured by:
- 93% improvement in first-time-right performance
- 90% increase in asset availability
- 88% improvement in on-time delivery schedule adherence
By another measure, with over 50% of employee time saved across key workflow areas like production throughput and quality assurance, companies are repurposing workforce capacity toward higher-value initiatives, like:
- 36% prioritizing workforce safety, training and operational compliance
- 35% optimizing asset performance and reliability
- 26% accelerating continuous process improvement
- 25% growing overall market share
In contrast, executive leadership’s primary AI effort over the same period was upskilling management to improve their own AI literacy (41%), directing attention inward rather than enabling the floor. While 27% of respondents view AI literacy as the first vital step for organizational readiness, ground-level execution is moving regardless, leaving leadership confidence (30%) as one of the biggest operational barriers to scaling success.
That can be a problem because in industrial operations, this gap between confidence and control is an operational liability. Agentic AI at scale without robust safety frameworks and decision oversight creates compounding risk: unvalidated outputs in mission-critical processes, uncontrolled data exposure, decisions without human accountability.
“The factory floor is moving at full speed. Workers see the operational insights, know their data better than anyone, and they know they need industrial-grade AI solutions to turn that expertise into action,” Cathie Hall, Chief Product & Customer Officer at IFS, said in a release. “The real challenge for leadership isn’t driving adoption, it’s having the insights to clear legacy roadblocks and delivering the secure industrial harness, data pipelines, and governance required to scale these wins safely and globally.”
