Exploring Agentic AI in GxP Enterprise Asset Management A practical look at how agentic AI can break down data silos, strengthen compliance, and reshape asset management across life sciences operations.
Siloed systems, manual handoffs, and reactive processes continue to slow down life sciences operations — driving downtime, delaying responses, and adding compliance risk. Agentic AI is starting to change that, but adoption in GxP environments comes with real questions around validation, data integrity, integration, and trust.
In this on-demand session, Bill Lucas and Peter Swanson from Blue Mountain explore where agentic AI fits into Enterprise Asset Management today, how to adopt it in a risk-controlled way, and what a human-in-the-loop future looks like across EAM, QMS, ERP, MES, and historian systems.
What you’ll take away
- A three-phase maturity model for agentic AI — assist, augment, and automate
- Three integration architectures — embedded, RAG-enabled, and middleware orchestration — and when each one fits
- A risk-tiered view of agent actions (low, moderate, high) and how to design controls, oversight, and guardrails for each
- A five-step validation loop — boundaries, test scenarios, behavior verification, human review, and evidence — aligned with GAMP 5 v2, ISO 42001, EU Annex 22, and the EU AI Act
- Practical first use cases, including automated documentation, deviation detection, and root cause analysis as a path toward predictive maintenance
- Adoption considerations: API readiness, least-privilege security, governance gates, model hosting, and end-to-end auditability
- Peer benchmarks from live audience polls on data maturity, top AI concerns, and the highest-value EAM use cases
Whether your organization is just evaluating agentic AI or actively shaping a roadmap, this session delivers a grounded, GxP-ready perspective you can apply immediately. Includes audience Q&A.
Who should attend
- Directors of Quality
- Validation Leaders
- Maintenance and Facilities Managers
- Reliability Engineers
- IT Leaders supporting GxP systems
- Operations and Manufacturing Leaders
- Digital Transformation and AI/ML Leaders in life sciences
Speakers
Bill Lucas — Chief Platform Architect, Blue Mountain Bill has more than 21 years of experience in enterprise technology, including custom system design, corporate network architecture, and large-scale application development. With over 18 years focused on calibration and maintenance software in regulated life sciences environments, he brings practical insight into building scalable, compliant asset management platforms.
Peter Swanson — Principal AI Engineer, Blue Mountain Peter leads the design of AI capabilities within Blue Mountain’s Regulatory Asset Manager (RAM) platform, focusing on how agentic AI can be applied safely inside GxP-regulated environments. His work centers on validation, observability, and human-in-the-loop architectures that help life sciences teams progress from AI-assisted workflows to selective automation without compromising compliance.