NEW RESEARCH from Netskope Threat Labs has found that 83% of AI-related security violations in manufacturing involve employees sharing information with AI tools in ways that breach company policies. This makes it the most prevalent AI-related security risk facing manufacturers, with employees potentially exposing confidential documents or sensitive company data through their use of AI applications. 

Regulated data, such as personal or financial information subject to legal protection, is the most common type of sensitive information involved in AI-related data policy violations, accounting for 57% of recorded events. Passwords and API keys follow at 19%, intellectual property at 16% and source code at 9%. 

While protecting sensitive information remains a challenge, manufacturers are making progress in bringing AI use under corporate control. The share of users adopting organisation-managed AI applications has doubled from 35% to 70% over the past year, while personal AI account use fell from 75% to 55%. However, the share of users switching between personal and enterprise accounts rose from 9% to 25%, suggesting that shadow AI remains a growing challenge, even as manufacturers gain greater control over AI use. 

This shift comes as AI adoption accelerates across manufacturing, with active AI use rising from 40% to 67% over the past year. AI is also becoming part of everyday business applications, with 96% of employees using software containing AI-powered features and 90% interacting with systems that use customer or user data to train models.  

Beyond the applications employees use, manufacturers also need to consider how AI connects with other systems. Connections between AI tools and external systems are growing rapidly, with the number of automated connections to remote servers rising by 490% and interactions increasing by 600%. As AI becomes more integrated into everyday operations, manufacturers need to understand what information these tools can access and where it goes. 

“Manufacturing organisations have moved well beyond initial trials with basic AI tools. We are seeing a clear transition toward deep operational integration, led by enterprise-managed solutions such as Microsoft Copilot and developer platforms such as Anthropic, alongside a sharp rise in automated MCP connections,” said Gianpietro Cutolo, cloud threat researcher at Netskope. “While this adoption drives significant efficiency, it also introduces crucial security challenges around non-human entities and data governance that security teams must proactively address.” 

To learn more about AI adoption, data security and cloud threats across the manufacturing sector, download the Netskope Threat Labs Manufacturing Report 2026.