Faculty: Charles Paul | Code: FDB1603
This webinar provides a detailed and operationally focused approach to preparing organizations to defend their use of artificial intelligence during regulatory inspections and audits by aligning AI use with established quality system expectations and ensuring that it can be clearly explained, supported, and justified under scrutiny.
The session begins by examining how inspections actually unfold in practice, starting with high-level evaluation of the quality system and progressing into detailed process walkthroughs, document reviews, and personnel interviews. Participants will see how inconsistencies between procedures, documentation, and explanations often reveal the presence of AI even when it is not explicitly disclosed. AI use typically becomes visible through gaps in traceability, differences in how processes are described, and outputs that appear structured but lack clear evidence of how they were developed. The webinar then identifies specific trigger points where AI involvement is most likely to surface, including SOP development and revision processes, CAPA and deviation investigations, training material creation, and data summarization activities. Participants will learn how these trigger points lead inspectors to probe deeper into process control, accuracy, and accountability.
A central focus of the session is defining what constitutes a defensible position when AI is part of a quality system process. Defensibility is not based on the absence of AI, but on the ability to demonstrate control over its use. This includes clearly defining how AI is used within procedures, establishing boundaries for where it can and cannot be applied, ensuring that all outputs are reviewed and verified at a level appropriate to their risk, and maintaining clear accountability with qualified personnel responsible for final decisions. The webinar explores each of these elements in detail, including the types of evidence inspectors expect to see and the common ways organizations fail to meet these expectations when there is a disconnect between documented procedures and actual practice. Particular emphasis is placed on maintaining alignment between documented processes and real-world execution.
The session also addresses personnel readiness, highlighting the importance of consistent and accurate explanations during inspection. Even when procedures exist, inconsistent responses from staff are often interpreted as evidence of uncontrolled processes. Participants will learn how to prepare personnel to describe AI use in a way that aligns with documented procedures and reflects actual execution. In addition to personnel readiness, the webinar examines documentation readiness, focusing on ensuring that SOPs accurately reflect workflows, that records demonstrate how outputs were generated and verified, and that investigation files clearly show evidence-based conclusions rather than unsupported summaries.
Common failure scenarios are analyzed in detail, including acceptance of AI-generated content without sufficient review, lack of traceability for how content was developed, and inconsistent application of AI across similar processes. The session concludes with a practical readiness approach that includes conducting internal assessments of AI use, identifying gaps between current practice and documented procedures, prioritizing corrective actions, and preparing for inspection questioning. The overall objective is to ensure that AI use is fully integrated into the quality system in a way that is transparent, consistent, and defensible under real inspection conditions.
Most organizations do not believe they are using artificial intelligence in a way that impacts regulatory compliance, but in practice AI is already influencing critical quality system activities without formal recognition or control. SOP authors use AI to draft content, investigators use it to summarize deviation data, and training teams use it to develop materials, often without defined procedures, consistent application, or documented oversight.
Inspectors are not going to ask whether AI is being used; they are going to evaluate how processes are performed, how accuracy is ensured, and who is responsible for the outcome. When AI has influenced a process and its use is not clearly defined, consistently applied, and properly verified, the process appears uncontrolled. This leads to loss of confidence in documentation, questions about the validity of investigations, and increased scrutiny of the overall quality system.
The risk is compounded by the fact that many organizations believe they have control, but that control is often informal, inconsistently applied, or not aligned with actual practice. Different personnel may describe the same process in different ways, documentation may not reflect how work is truly performed, and accountability for AI-assisted outputs may be unclear. During an inspection, these inconsistencies are quickly identified and can trigger deeper investigation into process control.
This webinar addresses these challenges directly by providing a structured approach to identifying where AI is being used, aligning that use with defined procedures, ensuring documentation reflects actual execution, and preparing personnel to provide consistent, accurate, and defensible explanations during inspection. The goal is not to eliminate AI, but to ensure that its use can be clearly explained, justified, and defended under regulatory scrutiny without creating additional risk.
Artificial intelligence is now being used across quality systems in regulated environments—often in ways that are not formally defined or consistently controlled. Tools such as ChatGPT are being applied to draft SOPs, summarize deviations, support CAPA investigations, generate training content, and assist with regulatory documentation. While these applications can improve efficiency, they introduce a critical shift: the method by which information is generated and decisions are supported is changing, but regulatory expectations are not.
Regulatory agencies, including the U.S. Food and Drug Administration, do not evaluate tools in isolation. They evaluate whether:
If AI is used within a process, it becomes part of that process. If it is not defined, controlled, and supported by documentation, it effectively exists outside the quality system—even if it is widely used. This creates a disconnect between how work is actually performed and how it is represented during inspection. This webinar focuses on closing that gap—ensuring that AI use is not only controlled, but explainable, consistent, and defensible under direct regulatory scrutiny.
Charles H. Paul is the President of C. H. Paul Consulting, Inc. - a regulatory, manufacturing, training, and technical documentation consulting firm - celebrating its twentieth year in business in 2017. He has been a regulatory and management consultant and an Instructional Technologist for 30 years and has published numerous white papers on various regulatory and training subjects. The firm works with both domestic and international clients designing solutions for complex training and documentation issues. He has held senior positions in consulting and in corporate training development prior to forming C. H. Paul Consulting, Inc. He also worked for several years in government contracting managing the development of significant Army-wide training development contracts impacting virtually all of the active Army and changing the training paradigm throughout the military. He has dedicated his entire professional career explaining the benefits of performance-based training