As IT and OT teams work more closely together, cyber risks become more visible, not smaller—an essential step toward building resilient, AI-ready industrial environments, Cisco stated. Yet today, only 20% of organizations report fully collaborative IT/OT interworking on cybersecurity, the report states.
The 2026 report also shows how quickly AI has become the main topic of conversation among industrial networking teams. For example, the survey found 61% of respondents are actively deploying AI in industrial environments, and only 20% report mature, scaled adoption. Interestingly, in its 2024 report, Cisco found that a shortage of skilled workers was the number one challenge facing AI adoption. That challenge has fallen to third place in 2026, with AI technology integration capturing the second slot.
Some other insights from the Cisco research include:
- 51% of respondents anticipate significant increases in connectivity and reliability requirements, while 96% say wireless networking reliability is critical to enabling industrial AI—making it foundational to network readiness at scale.
- Greater edge compute capacity (44%), bandwidth (42%), and mobility (40%) are top network requirements for AI at scale.
- AI workloads introduce new performance, power, and reliability requirements that exceed traditional industrial network design assumptions. Among respondents, 97% expect AI workloads to have an impact on their industrial networks.
- Scaling AI requires shifting from human-in-the-loop workflows to machine-to-machine decisioning— driving investment in connectivity, edge, and data infrastructure.
- Effective collaboration between IT and OT teams directly impacts AI outcomes. But 43% continue to operate with limited or no IT/ OT cooperation. Disparate teams slow AI deployment and increase operational risk, while IT/OT alignment accelerates scalability, stability, and security.
IBM’s X Force security outfit recently wrote that AI is no longer an emerging concept in cybersecurity: “It’s a force multiplier actively used by both defenders and adversaries. Threat actors are already applying generative AI to scale phishing operations, accelerate malicious code development and enhance social engineering through improved language quality and realism. At the same time, defenders are using AI-driven analytics to process vast volumes of telemetry, identify anomalous behavior and shorten detection and response timelines.”
