AI is well out of experimental stages and into embedded operational reality in U.S., U.K., report finds

A report out this month from “cyberhardening” technology company RunSafe Security has encouraging news about the penetration of AI into embedded systems (but not the security of those systems when AI intrudes), joining the cacophony of recent reports showing AI’s penetration of manufacturing but its data and cybersecurity limitations and concerns.

RunSafe surveyed more than 200 embedded engineers and security professionals in the U.S., the U.K., and Germany, joining one by Amazon Web Services and India firm Tata Consultancy Services, the results from which were released earlier this month, that polled a similar number across North America and Europe on the question of AI in manufacturing operations and systems.

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The message from RunSafe: AI is well-embedded by now but security in these systems is struggling to keep pace. Some highlights from McLean, Virginia-headquartered RunsSafe:

• 80.5% of respondents use AI tools in embedded development.
• 83.5% have deployed AI-generated code into production systems.
• 93.5% expect AI usage to grow in the next two years.
• 53% cite security as their top concern with AI-generated code.
• 73% rate the cybersecurity risk as moderate or higher.

According to the RunSafe Security report, AI-generated code is running in production across medical devices, industrial control systems, automotive platforms, and energy infrastructure.

The report also found that AI has moved from experimental curiosity to an operational reality in embedded systems development.

“AI will transform embedded systems development with teams deploying AI-generated code at scale across critical infrastructure, and we see this trend accelerating,” said Joseph Saunders, RunSafe’s founder and CEO.

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“Our report reveals an industry at an inflection point, where transformation is happening faster than security practices have evolved. Organizations that navigate it successfully will be those that maintain the same rigor with AI-generated code that they've traditionally applied to human-written code while also recognizing that AI introduces new patterns, risks, and security requirements.”

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The AWS/Tata Consultancy study veered from the cybersecurity hazards of AI adoption and straight toward the sheer rush toward adoption—and the peril of data unprepared to support the technology.

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Also according to that joint report, titled Future-Ready Manufacturing Study 2025, of the 216 senior manufacturing leaders in North America and Europe surveyed, half said their organization’s digital transformation spending in the next two years will go toward adoption.

Only about a fifth—21%—said their operations were fully AI-ready, however, primarily due to data infrastructure obstacles.

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That makes for a lot of adoption headaches along the way, as many experts predict.

However, fully three-quarters—exactly 75%—of these manufacturing leaders polled in that report expect AI to become a top-three margin driver by next year, with 88% anticipating the technology will capture at least 5% of operating margin.