Understand how FDA enforcement actions on AI are reshaping compliance expectations — and what your organization must do to stay inspection-ready.
Includes live access & recording
Artificial Intelligence is rapidly transforming regulated industries — from automated quality reviews and predictive maintenance to complaint handling and CAPA management. However, with innovation comes regulatory scrutiny.
The FDA's first Warning Letter involving the use of AI has become a defining moment for GMP-regulated organizations, signaling that regulators expect AI-enabled processes to be validated, controlled, monitored, and fully integrated into the organization's Quality Management System (QMS).
This webinar explores the implications of FDA enforcement actions related to AI and explains what organizations must do to maintain compliance while adopting advanced technologies. Participants will gain insight into how FDA expectations for data integrity, validation, risk management, change control, and oversight apply to AI-driven systems.
By understanding the regulatory landscape surrounding AI, organizations can confidently leverage innovation while maintaining patient safety, product quality, and operational excellence.
AI adoption in regulated industries is accelerating, but many organizations remain unclear about FDA expectations regarding validation, oversight, documentation, and risk management.
The FDA's first AI-related Warning Letter demonstrates that regulators are closely evaluating how companies implement and control AI-enabled systems within their quality operations.
This session provides practical guidance for understanding the compliance risks associated with AI and the steps organizations should take to ensure their quality systems remain inspection-ready.
By the end of this session, participants will be equipped to address the full compliance lifecycle of AI in regulated environments.
Understand the significance of the FDA's first AI-related Warning Letter.
Identify FDA expectations for AI governance within GMP-regulated environments.
Learn how AI impacts quality systems, validation, and data integrity requirements.
Apply risk-based approaches for AI implementation and oversight.
Understand documentation and change control requirements for AI-enabled systems.
Evaluate AI-related risks including bias, cybersecurity, and automated decision-making.
Develop strategies for integrating AI into CAPA, deviation management, and quality operations.
Prepare for regulatory inspections involving AI-driven technologies.
Four focused areas that will transform how your organization approaches AI compliance.
Understand the significance of the FDA's first AI-related Warning Letter and its far-reaching impact on GMP-regulated industries.
Learn how AI systems should be validated, monitored, and controlled within a compliant Quality Management System.
Discover approaches for managing AI-related risks including bias, data integrity, cybersecurity, and change management.
Gain actionable recommendations for integrating AI into quality operations while maintaining full regulatory oversight.
A comprehensive deep-dive across 12 critical areas of AI compliance in regulated environments.
Professionals across quality, compliance, and technology roles in pharmaceutical, biotech, medical device, and life sciences organizations.
Quality Assurance
Regulatory Affairs
Validation & CSV Specialists
Compliance Officers
Manufacturing & Operations
IT & Digital Transformation Managers
CAPA & Deviation Management Teams
Data Integrity Specialists
Risk Management Professionals
Internal Auditors & Inspection Readiness Teams
Executive Leadership Evaluating AI Strategies
The use of Artificial Intelligence in regulated industries is accelerating rapidly. However, the FDA's first Warning Letter citing AI-related violations has made it clear that deploying AI tools without proper governance, validation, and documentation can have serious regulatory consequences. Organizations that rush to implement AI without understanding the applicable regulatory framework are placing their operations — and ultimately patient safety — at risk.
Current FDA regulations — including 21 CFR Part 11, Part 210/211, Part 820, and the emerging AI/ML Action Plan — require that any software used in regulated decision-making be validated, controlled, and transparent. When AI is integrated into quality systems without meeting these standards, it can compromise data integrity, undermine audit trails, and create unverifiable conclusions that regulators cannot accept.
This session also looks ahead — as FDA continues to build its AI oversight capabilities and issue new guidance, companies must be proactive. A well-designed AI governance framework that incorporates validation, human oversight, change control, and continuous monitoring is not just a compliance requirement; it is an operational imperative for any organization seeking to harness AI's potential while maintaining regulatory trust and product quality.
Dr. Ginette Collazo is an Industrial-Organizational Psychologist with over 20 years of experience specializing in Engineering Psychology and Human Reliability. She is the founder and CEO of Human Error Solutions (HES), a Florida-based consulting firm established with a focus on human error reduction, behavior-based safety, and regulatory compliance in the pharmaceutical and life sciences industries.
Dr. Collazo is the author of Human Error: Root Cause Determination Model (2008), a widely referenced framework for investigating human performance failures in regulated environments. She has presented at numerous industry conferences including Interphex, FDAnews Annual Conference, and the Global Conference on Process Safety.
Her expertise in AI governance and quality system management, combined with her deep understanding of human factors and regulatory expectations, makes her uniquely positioned to address the critical intersection of AI adoption, data integrity, and FDA compliance in today's life sciences landscape.
Don't miss this critical training on FDA's evolving AI enforcement landscape. Secure your spot and make your quality system inspection-ready.