Laboratory software supports highly specialized scientific work, but everyday tasks can still involve navigating multiple applications, menus, and setup steps. Waters AI Link introduces a more intuitive way to interact with waters_connect Software, allowing scientists and laboratory teams to use natural language to access supported capabilities and turn requests into defined actions within their analytical workflows. 

Built using the open Model Context Protocol (MCP) standard, Waters AI Link converts waters_connect Software capabilities into AI-accessible tools.

This supports activities like:

• Creating and editing sample lists
• Working with acquisition methods
• Assigning instruments
• Submitting work
• Accessing analytical results
• Generating reports 

Instead of manually navigating every individual step, scientists can describe what they want to accomplish conversationally while Waters AI Link connects that request with the appropriate capabilities in waters_connect Software.

Importantly, this more intuitive experience does not mean giving AI unrestricted access to the laboratory. Every action remains subject to waters_connect Software authentication, permissions, and access controls, meaning users can only perform actions through AI that they are already authorized to perform directly. The laboratory's scientific applications and validated assets remain in place, with AI providing a new way to interact with those established capabilities. 

By combining natural-language interaction, an open architecture, and platform-level controls, Waters is building a foundation that can expand as more capabilities become available, helping move laboratory AI from experimentation toward a practical part of everyday scientific work. 

For regulated laboratories, realizing the potential of AI means balancing innovation with the requirements that protect product quality, data integrity, and, ultimately, patient safety. As AI and machine learning become part of pharmaceutical laboratory workflows, established principles including data governance, risk management, validation, transparency, traceability and human oversight remain fundamental.

Regulatory expectations are also evolving alongside the technology. FDA and EMA guidance increasingly addresses the use of AI across drug development and regulated environments, including expectations around model transparency, data governance, lifecycle management, validation, and human oversight. For QC laboratories, the opportunity is therefore not simply to adopt AI faster, but to introduce it in ways that preserve scientific rigor, reproducibility, and appropriate control.

Waters is helping laboratories understand this changing landscape and the considerations that accompany AI adoption in GMP environments. From establishing strong data foundations and an appropriate governance framework to preparing for regulatory inspection, our experts explore the practical steps that organizations should consider as they build greater AI maturity.

Explore AI and compliance in the regulated laboratory: 

• AI in GMP: Navigating Evolving Expectations for Regulated Labs
• Is Your Organization Ready for AI Inspection?
• AI Maturity in GMP: Accelerating Your Digital Journey at Warp Speed, Safely