Five Best Practices for Using AI in FDA-Regulated Communications
Date: November 5, 2026
Duration: 60 Minutes
Time: 12 PM EST
Five Best Practices Covered
1. Establish Risk-Based Boundaries for AI-Assisted Communications
- Distinguish routine administrative assistance from communications that could affect regulatory commitments, clinical decisions, product quality, or patient safety.
- Determine which activities can be permitted, which require expert approval, and which should be restricted.
Establish approval authority and escalation criteria for higher-risk outputs.
2. Prevent Unsupported Regulatory Interpretations and Misleading Conclusions
- Assess AI-generated interpretations of FDA regulations, guidance, inspection observations, and agency correspondence.
- Identify fabricated citations, outdated requirements, unsupported claims, and conclusions that exceed the available evidence.
Establish verification expectations before AI-assisted content is used in regulatory responses, submissions, or formal communications.
3. Maintain Document Integrity, Traceability, and Record Control
- Determine when AI-assisted drafts, summaries, analyses, and final communications require documentation or retention.
- Address version control, source traceability, review evidence, and the preservation of material decisions.
Consider how AI-generated content should be handled when it contributes to controlled documents or records governed by applicable electronic-record and record-retention requirements.
4. Define Human Oversight, Review Responsibilities, and Accountability
- Establish who is responsible for reviewing, approving, and releasing AI-assisted content.
- Determine when independent review, cross-functional approval, or additional verification is warranted.
Address how organizations should handle errors, unauthorized AI use, and deficiencies discovered after communication or release.
5. Integrate AI Controls into Quality Systems and Inspection Readiness
- Determine how AI-use policies, risk assessments, training, vendor assessments, and corrective actions fit into existing governance and quality processes.
- Assess whether current controls adequately address confidentiality, tool changes, output reliability, and employee use of unapproved platforms.
Prepare to explain how AI-assisted work is controlled, reviewed, and corrected when relevant questions arise during an audit or inspection.
What Will You Learn?
By attending this webinar, you will gain a practical perspective on how to:
- Develop risk-based criteria for approving AI use across regulatory, clinical, and quality functions.
- Set review and escalation requirements based on the consequences of an incorrect communication.
- Evaluate AI-generated regulatory claims against authoritative source documents and current requirements.
- Determine appropriate documentation and traceability for AI-assisted work.
- Assign responsibility for reviewing, approving, and correcting AI-assisted outputs.
- Identify gaps in existing policies, procedures, training, and quality controls.
- Assess AI-related risks when selecting vendors or introducing new tools into established workflows.
Prepare a defensible approach to demonstrating oversight of AI-assisted communications.
Who Will Benefit?
This webinar is intended for professionals responsible for regulatory compliance, clinical operations, quality systems, and organizational oversight, including:
- Regulatory Affairs Managers, Directors, and Heads of Regulatory Affairs.
- Clinical Operations Directors and Clinical Trial Managers.
- Quality Assurance Managers, Directors, and Heads of Quality.
- GCP, GMP, and compliance leaders.
- Regulatory and medical writers involved in formal regulatory documentation.
- Pharmacovigilance, clinical data management, and medical affairs professionals.
Senior management responsible for AI adoption, risk oversight, and compliance governance.
Overview
Artificial intelligence is already changing how life sciences organizations prepare regulatory correspondence, review clinical documentation, investigate quality events, manage controlled documents, and communicate across functions. The challenge for senior management is no longer whether employees can use AI. It is how to capture its benefits without introducing weaknesses into regulated processes. An AI-generated statement may sound authoritative yet misinterpret an FDA requirement. A meeting summary may omit a critical decision. A draft CAPA response may overlook the underlying root cause, while an AI-assisted regulatory submission or clinical report may contain inconsistencies that escape routine review. Confidential information may also be exposed through tools that have not been appropriately assessed.
For regulatory, clinical, and quality leaders, these are not simply technology concerns. They raise questions about decision authority, document control, review responsibilities, data integrity, risk management, and the organization’s ability to demonstrate effective oversight. This webinar examines five management-level practices for controlling AI-assisted communications in FDA-regulated environments. Rather than introducing AI tools or basic prompting techniques, the session focuses on where controls are needed, how review should be proportionate to risk, what evidence should be retained, and how organizations can establish clear accountability when AI contributes to regulated work.
Why Should You Attend?
The real challenge is not detecting every AI error manually. It is designing a process in which consequential errors are less likely to reach an investigator, regulator, clinical decision-maker, or controlled quality record. Senior professionals must make practical decisions: Which AI-assisted activities can be permitted with routine review? Which require subject-matter expert approval? When should AI-generated content be rejected, escalated, or documented? How should organizations respond when an error is discovered after the content has been circulated or incorporated into a regulated record? This session will examine these questions through the perspectives of regulatory affairs, clinical operations, and quality assurance. It will help attendees think beyond generic AI policies and focus on controls that can be implemented, assigned to accountable owners, and evaluated for effectiveness.
The trainer, Dr. Mukesh Kumar, will discuss various scenarios, including AI-assisted FDA responses, AI-generated clinical meeting summaries, and AI-assisted deviation or CAPA documentation, to highlight potential regulatory and quality risks, the importance of human oversight and verification, and practical approaches to ensuring accuracy, traceability, and accountability in AI-assisted communications.
Speaker: Mukesh Kumar
PhD, RAC | CEO, FDAMap
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