Artificial Intelligence (AI) is rapidly becoming part of daily operations in GMP-regulated industries, from automated documentation reviews and predictive analytics to deviation investigations and training systems. While many organizations are still exploring how to implement AI effectively, the FDA is already expecting companies to apply existing GMP principles to these technologies—even before formal AI-specific regulations are fully established.
This webinar examines the current FDA expectations surrounding AI use in regulated environments and explains how organizations can proactively prepare their quality systems for inspection readiness. Participants will learn how FDA expectations for validation, data integrity, risk management, supplier oversight, and human accountability already apply to AI-enabled systems.
The session will provide practical guidance on how to responsibly implement AI within GMP operations while maintaining compliance, transparency, and quality oversight. Attendees will also explore common compliance gaps organizations may overlook when deploying AI tools across quality and manufacturing systems.
By understanding what regulators already expect, organizations can avoid costly mistakes, strengthen governance practices, and build sustainable AI strategies aligned with GMP requirements.
This webinar will help attendees understand how existing GMP expectations apply to AI systems and what organizations should be doing now to avoid compliance risks.
Professionals responsible for quality, compliance, digital transformation, validation, and operational excellence in regulated industries, including:
This webinar examines the current FDA expectations surrounding AI use in regulated environments and explains how organizations can proactively prepare their quality systems for inspection readiness. Participants will learn how FDA expectations for validation, data integrity, risk management, supplier oversight, and human accountability already apply to AI-enabled systems.
The session will provide practical guidance on how to responsibly implement AI within GMP operations while maintaining compliance, transparency, and quality oversight. Attendees will also explore common compliance gaps organizations may overlook when deploying AI tools across quality and manufacturing systems.
By understanding what regulators already expect, organizations can avoid costly mistakes, strengthen governance practices, and build sustainable AI strategies aligned with GMP requirements.
WHY SHOULD YOU ATTEND?
Many organizations are adopting AI technologies faster than they are developing governance and compliance strategies to support them. Although FDA guidance on AI continues to evolve, inspectors already expect companies to demonstrate control, oversight, validation, and risk management for any system impacting product quality or patient safety.This webinar will help attendees understand how existing GMP expectations apply to AI systems and what organizations should be doing now to avoid compliance risks.
AREA COVERED
- Overview of AI Adoption in GMP-Regulated Industries.
- Current FDA Expectations for AI Use in Quality Systems.
- Applying Existing GMP Principles to Artificial Intelligence.
- AI Governance and Organizational Accountability.
- Validation Considerations for AI-Enabled Systems.
- Data Integrity and Audit Trail Expectations.
- Managing AI Risks: Bias, Hallucinations, and Model Drift.
- Supplier Qualification and Third-Party AI Oversight.
- Change Control and Lifecycle Management for AI Applications.
- Human Review and Decision-Making Responsibilities.
- AI Applications in CAPA, Deviations, Complaints, and Training.
- Inspection Readiness and Documentation Best Practices.
- Future Trends in AI Regulation and Compliance.
LEARNING OBJECTIVES
- Understand how current GMP regulations already apply to AI-enabled systems.
- Identify FDA expectations regarding AI governance and oversight.
- Learn validation considerations for AI-driven applications.
- Understand data integrity risks associated with AI technologies.
- Apply risk-based approaches for AI implementation within quality systems.
- Evaluate the role of human oversight in AI-assisted decision-making.
- Develop strategies for documenting and monitoring AI systems.
- Prepare organizations for regulatory inspections involving AI technologies.
- Regulatory Insight: Understand current FDA expectations for AI implementation within GMP-regulated operations.
- Inspection Readiness: Learn what inspectors may look for regarding AI governance, validation, and oversight.
- Risk Mitigation: Discover practical methods to manage AI-related risks including data integrity, bias, cybersecurity, and automated decision-making.
- Practical Compliance: Gain actionable strategies for integrating AI into quality systems while maintaining GMP compliance.
WHO WILL BENEFIT?
Professionals responsible for quality, compliance, digital transformation, validation, and operational excellence in regulated industries, including:
- Quality Assurance Professionals
- Regulatory Affairs Specialists
- Validation and CSV Teams
- Compliance Managers and Directors
- Manufacturing and Operations Leaders
- IT and Digital Transformation Professionals
- CAPA and Deviation Management Teams
- Data Integrity Specialists
- Risk Management Professionals
- Internal Auditors and Inspection Readiness Teams
- Executive Leadership Evaluating AI Adoption.
Many organizations are adopting AI technologies faster than they are developing governance and compliance strategies to support them. Although FDA guidance on AI continues to evolve, inspectors already expect companies to demonstrate control, oversight, validation, and risk management for any system impacting product quality or patient safety.
This webinar will help attendees understand how existing GMP expectations apply to AI systems and what organizations should be doing now to avoid compliance risks.
This webinar will help attendees understand how existing GMP expectations apply to AI systems and what organizations should be doing now to avoid compliance risks.
- Overview of AI Adoption in GMP-Regulated Industries.
- Current FDA Expectations for AI Use in Quality Systems.
- Applying Existing GMP Principles to Artificial Intelligence.
- AI Governance and Organizational Accountability.
- Validation Considerations for AI-Enabled Systems.
- Data Integrity and Audit Trail Expectations.
- Managing AI Risks: Bias, Hallucinations, and Model Drift.
- Supplier Qualification and Third-Party AI Oversight.
- Change Control and Lifecycle Management for AI Applications.
- Human Review and Decision-Making Responsibilities.
- AI Applications in CAPA, Deviations, Complaints, and Training.
- Inspection Readiness and Documentation Best Practices.
- Future Trends in AI Regulation and Compliance.
- Understand how current GMP regulations already apply to AI-enabled systems.
- Identify FDA expectations regarding AI governance and oversight.
- Learn validation considerations for AI-driven applications.
- Understand data integrity risks associated with AI technologies.
- Apply risk-based approaches for AI implementation within quality systems.
- Evaluate the role of human oversight in AI-assisted decision-making.
- Develop strategies for documenting and monitoring AI systems.
- Prepare organizations for regulatory inspections involving AI technologies.
- Regulatory Insight: Understand current FDA expectations for AI implementation within GMP-regulated operations.
- Inspection Readiness: Learn what inspectors may look for regarding AI governance, validation, and oversight.
- Risk Mitigation: Discover practical methods to manage AI-related risks including data integrity, bias, cybersecurity, and automated decision-making.
- Practical Compliance: Gain actionable strategies for integrating AI into quality systems while maintaining GMP compliance.
Professionals responsible for quality, compliance, digital transformation, validation, and operational excellence in regulated industries, including:
- Quality Assurance Professionals
- Regulatory Affairs Specialists
- Validation and CSV Teams
- Compliance Managers and Directors
- Manufacturing and Operations Leaders
- IT and Digital Transformation Professionals
- CAPA and Deviation Management Teams
- Data Integrity Specialists
- Risk Management Professionals
- Internal Auditors and Inspection Readiness Teams
- Executive Leadership Evaluating AI Adoption.