Bryan Carmichael

Highly regulated sectors - from life science to financial services - demand zero tolerance for failure when deploying AI. In these environments, “close enough” is never good enough. During this session, Bryan Carmichael, Director of Digital Innovation & Data Science explores how ThermoFisher are building robust AI infrastructures that adhere to regulatory issues, ensure auditability,

and guarantee repeatability.

• Designing AI systems where precision, not probability, is the standard
• Choosing tools and data pipelines that ensure regulatory compliance
• Integrating human-in-the-loop mechanisms for validation and control
• Collaborating effectively with regulators, auditors, and legal advisors

AI foundations lie in robust, secure, and intelligent data platforms that can fuel innovation while preserving trust and control. In this panel, senior data and AI leaders will explore what it takes to architect enterprise-grade data environments that support high-impact AI products. From governance to business outcomes, this session will unpack the intersection of data architecture and product strategy in the age of AI.

• The critical role of high-quality, actionable data in powering GenAI and AI applications
• Strategies to secure, manage, and maximize the value of enterprise data while preserving privacy and compliance
• Building data platforms that make information findable, accessible, trustworthy, interoperable, and reusable (FAIR)
• Operationalising data governance at scale through automation, policy enforcement, and platform design
• How AI is reshaping product development and business models – and what that means for data architecture going forward