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Rockwell finds life sciences manufacturers push AI & cyber

Rockwell finds life sciences manufacturers push AI & cyber

Fri, 2nd Oct 2026 (Today)
Raphael Veloso
RAPHAEL VELOSO News Editor

Rockwell Automation has published new research on digital transformation in life sciences manufacturing, finding that 90% of manufacturers in the sector now see it as necessary.

The report draws on responses from 104 managers and executives in 16 countries, spanning life sciences manufacturers, Original Equipment Manufacturers, system integrators and engineering procurement companies. It found that 58% of life sciences manufacturers have already deployed smart manufacturing technologies at scale or across parts of their operations.

The findings suggest companies are tying technology spending more closely to operational and commercial results, rather than treating it as a standalone modernisation effort. AI and machine learning were cited by 46% of respondents as the technologies most likely to deliver the biggest business outcomes, followed by process automation at 44% and cybersecurity at 39%.

Investment priorities were improving quality, cited by 43% of respondents, digitising operations at 36% and reducing risk at 35%. The report indicates that connected data, cybersecurity measures and validated AI applications are becoming central to improving visibility, strengthening quality processes and maintaining what it describes as continuous readiness.

AI and data

The research points to a gap between interest in AI and the use of underlying industrial data. Among respondents already using AI, 64% said they plan to expand its use within the next year, while 49% expect to increase investment over the next five years.

At the same time, only 32% said they effectively use more than half of the data they collect. That suggests many manufacturers are still building the data foundations needed to support broader AI use in regulated production environments.

Over the next 12 months, respondents said they plan to use AI and machine learning mainly for quality control, cybersecurity and process optimisation. Those uses were cited by 50%, 45% and 44% respectively.

Cyber risks

Cybersecurity also emerged as a major concern. More than half of life sciences organisations surveyed, 54%, said they had experienced at least one cyberattack in the past year.

The greatest exposure came from IT systems and enterprise networks, cited by 41% of respondents. Remote access and connected equipment followed at 33%, while IT and operational technology integration points were named by 29%.

The report argues that cyber resilience is no longer a separate compliance exercise for manufacturers in the sector. Instead, it describes system security as an ongoing requirement across the operating lifecycle as facilities become more connected and data flows expand across production, quality, engineering and business functions.

The report outlines seven actions for life sciences manufacturers seeking to build a stronger digital base for continuous readiness, including evidence management, cyber resilience, industrial data operations, defined AI use cases and AI governance.

Matt Weaver, Vice President, Global Industry - Life Sciences, Rockwell Automation, said manufacturers are changing how they approach compliance and operational preparedness.

"Manufacturers used to treat regulatory readiness as a project - something they ramped up for," said Matt Weaver, Vice President, Global Industry - Life Sciences, Rockwell Automation.

"Now, it has to be a daily discipline built into how the facility runs. The companies connecting their data, securing systems and validating AI deployments today are the ones that will be ready for what comes next from regulators or from the market," Weaver said.

The study forms part of Rockwell's 11th annual State of Smart Manufacturing research, which surveyed 1,560 decision-makers across industries in association with Sapio Research. Within that wider sample, the life sciences findings offer a snapshot of a sector under pressure to modernise operations while maintaining strict controls over data, quality and regulatory processes.