AI and Decision Making in GMP: Resolving Conflicts Between Human Judgment and AI Recommendations
Structures how GMP teams assess conflicting human and AI conclusions, assign decision authority, escalate disagreements, and document the final rationale under regulatory oversight.
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Regulatory expectations retain human accountability for AI-supported GMP decisions.
When AI and experienced personnel reach different conclusions, GMP teams need clear criteria for determining who decides, when escalation occurs, and why.
The session structures human review, authority boundaries, escalation criteria, bias assessment, and documentation practices around AI-supported quality and manufacturing conclusions.
AI-assisted GMP decisions require professionals to distinguish recommendation, review, override, escalation, and final accountability within a controlled decision process.
The session moves from the respective limitations of human and AI reasoning into Human-in-the-Loop roles, authority boundaries, and conflict resolution. It then addresses escalation criteria, cognitive bias, documentation of accepted or rejected recommendations, organizational policies, and the evidence surrounding final GMP conclusions during regulatory review.
- AI decision support across GMP operations
- Human-in-the-Loop decision structures
- Human and AI cognitive bias considerations
- Decision authority and accountability boundaries
- Criteria for accepting, challenging, or overriding AI output
- Escalation pathways for conflicting recommendations
- Documentation of AI-assisted GMP decisions
- FDA oversight and inspection considerations
Designed for professionals responsible for quality, manufacturing, compliance, risk, or technology decisions involving AI-supported GMP processes.
Dr. Ginette Collazo, Ph.D.
Dr. Ginette Collazo, Ph.D. brings over 30 years of regulated industry experience across pharmaceutical, laboratory, medical device, biologics, and related operations. Her work in quality consulting, regulatory assessments, inspections, recall support, and training gives her practical grounding in how analytical lifecycle expectations translate into documentation, quality decisions, and inspection-ready method management.
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Customized training is also available through TalkFDA Elite Training Labs.
This topic can also be delivered as a customized session for organizations seeking structured, implementation-focused training aligned with their internal processes and quality systems.
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