Industrial companies are moving rapidly from AI experimentation to real-world deployment, with 61% already deploying AI at scale, according to Cisco’s 2026 State of Industrial AI Report.
The report, which is based on a survey of more than 1,000 decision-makers across 19 countries and 21 industries, also found that improving productivity, reducing costs and enhancing security were the top goals of early adoption. More than eight out of 10 organizations plan to increase their AI investment.
Infrastructure is the biggest bottleneck to adoption. Nearly all respondents said AI workloads are increasing demands on connectivity, bandwidth and edge computing, while 96% identified reliable wireless networks as critical to success. Network readiness is now a determining factor in whether AI deployments can scale.
Industrial companies such as manufacturers, utilities, energy providers, automakers and the like often use internet-connected machinery and robots where wireless networks serve as a vital link to sensors that continuously collect operational data for analysis.
The report said use cases such as process automation, supply chain optimization and predictive maintenance dominate, though firms increasingly plan to expand into resilience-focused applications.
Cybersecurity presents a paradox. It is the top barrier to adoption, cited by 40% of respondents, but also a key enabler, with 85% expecting AI to strengthen their cybersecurity posture.
Organizational alignment is another hurdle. About 43% of companies still report limited collaboration between IT and operational technology teams, slowing deployment and increasing risk.
Looking ahead, 93% of organizations express confidence in scaling AI, but most expect incremental improvements rather than full operational transformation over the next three to five years.