ORLANDO, Fla.—IFS revealed new research here that shows a divide between immediate factory-floor-level industrial AI execution and C-suite strategies for the technology, as operational workers are driving real AI implementation while leadership catches up on governance, AI safety, and how to scale the technology longer term.  

At its annual conference, IFS Unleashed, the industrial AI software provider announced findings that formal AI governance frameworks and data access structures aren't keeping up with real-world implementation by frontline workers, according to its Industrial Index 2026, which surveyed more than 2,200 senior decision-makers across 14 countries. 

Podcast: Realizing the full potential of connected worker solutions in the AI era

Frontline teams such as engineers, plant managers, service leads, and logistics managers connecting their domain expertise and operational data with industrial AI positively impacted performance, according to the IFS research. Rapid adoption of agents on factory floors also is delivering commercial returns across operational areas, and over 90% of organizations reported significant gains in reliability and performance, IFS found. 

For example, 93% reported improvement in “first-time-right" performance; 90% reported an increase in asset availability; and 88% reported improvement in on-time delivery schedule adherence.  

Companies also reported 50% of employee time saved across key workflow areas like production throughput and quality assurance, according to the IFS index. 

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However, as frontline workers have taken this transformation into their day-to-day operations over the past 12 months (43% of respondents had already trained in or had been introduced to agentic "digital workers"—with job titles such as dispatch assistant, service planning assistant, and time-entry manager), executive leadership is falling behind.  

Instead of enabling the floor, executive leadership’s primary AI effort was upskilling management to improve their own AI literacy (41%), directing attention inward, according to the index.  

Podcast: Realizing the full potential of connected worker solutions in the AI era 

While 27% of respondents viewed AI literacy as the first vital step for organizational readiness, ground-level execution is moving regardless, leaving leadership confidence as a barrier to scaling success at 30%.  

And while floor-level initiative indicates demand for AI tools, IFS found that the disconnect between perceived readiness and actual operational safeguards creates potentially dangerous exposure.  

For example, despite more than 70% of organizations claiming confidence in their safety and data policies, they are often missing critical controls: 

• Only 11% have validated AI outputs for safety-, quality-, or mission-critical processes.  
• Only 11% have established control mechanisms for AI use with sensitive or export-controlled data.  
• Only 4% have implemented mandatory human oversight or approval requirements for AI-supported decisions.  
• Only 20% have embedded industrial AI into supply chain management or maintenance planning. 

According to IFS, the gap between confidence and control is an operational reliability, as scaling agentic AI without safety frameworks and oversight creates risks like unvalidated outputs in mission-critical processes, uncontrolled data exposure and decisions without human accountability.

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“The factory floor is moving at full speed," said Cathie Hall, chief product and customer officer at IFS. "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."

She added: "To compete, leadership must match the frontline's pace. Companies that move now will compress decision cycles and extend competitive advantages. Leadership cannot afford to lag."