Research from Cisco has found that as many as two-thirds of industrial organisations have moved to active artificial intelligence (AI) deployments in live operational environments, yet while adoption momentum is strong, infrastructure and organisational alignment – especially networking and security – will dictate who achieves real transformation.
The latest version of the State of industrial AI report 2026 looked to provide a data‑driven view into how industrial organisations are adopting AI, the challenges they face as AI moves into live operations, and the opportunities created as AI becomes embedded in physical systems, infrastructure and workflows.
The study is based on data from a global survey of more than 1,000 operational technology decision‑makers, conducted by Cisco in association with Sapio Research. Respondents were from 19 countries and across 21 industry sectors, representing a range of industries including manufacturing, transportation, logistics, energy and utilities, and more. The study aggregated findings from decision-makers at companies with annual revenues of more than $100m.
Among the top findings were that AI organisations are harnessing AI to drive progress and overcome industry challenges, and that it is now delivering measurable operational benefits, in particular in use cases such as process automation, automated quality inspection, predictive maintenance, logistics and energy forecasting. Strong expected benefits from AI included productivity (59%), cost reduction (42%) and sustainability.
Industrial AI was seen to have moved from a future consideration to active deployment, with 61% of organisations now using AI in live industrial operations where performance, reliability and security have direct physical consequences, and 20% reporting scaled, mature deployments. Across manufacturing, transportation and utilities, AI was found to be powering machine vision, mobility, robotics and safety‑critical operations.
Most organisations indicated that they planned to increase AI spending (83%), and nearly nine in 10 expect meaningful outcomes in the next two years (87%). Yet just as adoption was accelerating, many firms were struggling to sustain and expand deployments, with readiness across network infrastructure, security and skills increasingly determining whether AI can scale consistently across core physical environments.
Indeed, network readiness and security posture were cited as the primary factors shaping how quickly and safely organisations scale AI across connected assets, machines and sites. The report observed that as AI becomes embedded in machines, sensors, vision systems and autonomous operations, organisations face rising demands for reliable connectivity, wireless mobility, predictable latency, edge compute and power, which were making network readiness a gating factor for physical AI deployments.
Just over half of firms (51%) expect significant increases in connectivity and reliability requirements in their industrial networks, and almost all firms (96%) noted that reliable wireless networks are vital for AI. In addition, 97% expected AI workloads to impact their industrial network requirements.
Yet while legacy infrastructure and skills gaps remain secondary challenges, Cisco also cautioned that the study also revealed many organisations were increasingly constrained by readiness gaps in networking infrastructure, cyber security and IT/OT operating models as AI shifts into real‑time, production‑grade use in physical environments.
Another key discovery was that organisations with closer collaboration between IT and operational teams report greater confidence in expanding AI, more stable networks supporting physical operations, and a stronger emphasis on cyber security as a baseline requirement, underscoring the need to build the skills required for scalable AI adoption.
Nearly two in three firms (57%) reported some level of IT/OT collaboration, while 43% reported limited or no collaboration. Just under half (47%) of organisations with limited IT/OT collaboration cited network instability as a top operational challenge to scale AI.
Cyber security was highlighted as shaping both the pace and confidence of AI adoption. Cisco also found that as AI expands connectivity and data flows across industrial environments, security remained the top barrier to scale. At the same time, organisations increasingly view AI as part of the solution, with a majority expecting AI to strengthen monitoring, detection and operational resilience.
“Industrial AI is moving from experimentation into production, where AI systems sense, reason and act in the real world,” said Vikas Butaney, senior vice-president and general manager of secure routing and industrial internet of things at Cisco. “At this stage, success is no longer determined by models alone, but by whether networks, security and teams are ready to support AI at the edge, in motion, and at scale. The research shows that organisations confident in scaling AI are those treating infrastructure, cyber security and IT/OT collaboration as foundational, not optional.”
