Rockwell Automation has warned that life sciences manufacturers are still struggling to match their digital ambitions with the data discipline and cyber safeguards needed to support them, even as smart manufacturing becomes more deeply embedded across the sector.
According to the company’s latest report, The New Operating Model for Life Sciences Manufacturing: Moving from Compliance to Continuous Readiness, 90% of life sciences manufacturers now see digital transform...
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ation as essential to their business. More than half, 58%, have already rolled out smart manufacturing technologies at scale or in parts of their operations, signalling that the industry is moving well beyond experimentation.
The report suggests that the main drivers are familiar: improving quality, digitising operations and lowering operational risk. Artificial intelligence and machine learning were identified as the technologies most likely to deliver meaningful business results, cited by 46% of respondents. Process automation followed at 44%, while cybersecurity came in at 39%, underscoring how closely efficiency gains and risk management are now linked in the sector.
Yet Rockwell’s findings also point to a gap between ambition and readiness. Among manufacturers already using AI, 64% plan to expand its use within the next 12 months and 49% expect to increase investment over the next five years. Even so, only 32% said they are effectively using more than half of the data they collect, suggesting that many organisations are generating information faster than they can organise, trust and apply it.
Cybersecurity remains another major pressure point. The report found that 54% of life sciences organisations experienced at least one cyberattack over the previous year. The most common exposure points were IT systems and enterprise networks, cited by 41% of respondents, followed by remote access and connected equipment at 33%, and IT/OT integration points at 29%. For a sector that increasingly relies on interconnected production environments, the findings highlight how digitalisation can widen the attack surface if security is not built in from the outset.
Matt Weaver, Rockwell Automation’s vice-president of global industry for life sciences, said in a company statement that the industry can no longer treat regulatory preparedness as a short-term exercise. “Manufacturers used to treat regulatory readiness as a project , something they ramped up for,” he said. “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.”
The report is based on responses from 104 managers and executives across life sciences manufacturers, original equipment manufacturers, systems integrators and engineering procurement companies in 16 countries. Rockwell argues that the results show a sector in transition: digital transformation is no longer framed as a future objective, but as a business necessity shaped by regulatory change, supply-chain pressure and the need for more resilient operations.
Rockwell says the next stage of maturity will depend less on how many technologies a company deploys, and more on how well those tools are tied together through a coherent operating model. In its view, the most effective manufacturers will be those that connect production, quality, engineering and business systems, creating a trusted data foundation that can support advanced analytics, continuous improvement and validated AI use cases.
To that end, the company sets out seven priorities for what it calls continuous readiness. These include digital evidence management for remote regulatory assessments and electronic records requests; cyber resilience for connected products and digital operations; industrial data operations built on standardised data models; and practical AI deployment with validation controls and human oversight. The list also covers quality by design in manufacturing, continuous software assurance for validated systems, and stronger knowledge management across the product lifecycle.
Rockwell recommends creating what it calls an inspection-ready evidence layer to support regulatory scrutiny. That would include secure access, curated exports, standard record packages and auditable trails so that batch records, deviations, corrective and preventive actions, change-control material, validation evidence and product quality reviews can be assembled quickly and with full context.
On cybersecurity, the report argues that resilience needs to be designed into connected products from development through to deployment and maintenance. It says stronger vulnerability management, clearer governance, better visibility and tighter supply-chain risk controls would help firms reduce exposure while maintaining operational continuity.
The company also places considerable emphasis on data architecture. It says manufacturers should be able to connect, contextualise and govern operational data across machines, processes and manufacturing systems, with standard metadata, lineage and access rules allowing information to be reused and traced reliably. In Rockwell’s view, this is a prerequisite not only for interoperability and visibility, but also for more dependable analytics and regulated AI applications.
For artificial intelligence, the report advises starting with lower-risk, well-defined use cases that support engineering work without replacing human judgement. Examples include helping to generate and review control code or identifying inconsistencies between specifications and logic. From there, firms could extend AI into process modelling, technology transfer, validation documentation, equipment performance and quality monitoring, provided intended use and validation requirements remain clear.
The report also argues that quality by design should be tied more closely to manufacturing execution, enabling processes proven at smaller scale to move more smoothly into clinical and commercial production. On software assurance, it points to automated testing, continuous integration and deployment controls where appropriate, and ongoing monitoring as ways of producing objective evidence while preserving oversight. Finally, it says product lifecycle management tools should connect development, technology transfer, manufacturing and post-approval change management so that knowledge is retained and applied more consistently across the product lifecycle.
Taken together, the findings suggest that life sciences manufacturers are embracing digital tools at pace, but still face a more difficult task: turning investment into a stable, secure and inspectable operating model. Rockwell’s message is that the winners will not simply be those that digitise fastest, but those that build the discipline to sustain those systems under regulatory, operational and cyber pressure.
Source: Noah Wire Services
