AI in Food Safety: Ethical and Efficient Food Safety Document Writing

This workshop introduces participants to the use of Artificial Intelligence (AI) tools for writing and refining food safety documents (Standard Operating Procedures (SOPs), policies, plans) within food safety programs. The course provides opportunities and challenges associated with AI-assisted documentation. We will specifically explore both efficiency and ethical considerations through a combination of presentations, discussion, and hands-on practice. Participants will explore how AI can streamline document development by assisting with drafting, editing, and updating compliance-ready procedures that align with regulatory standards such as 21 CFR 117 and GFSI audit requirements.

Attendees will gain hands-on experience using AI to generate document drafts, edit and revise prior versions, experiment with different prompt engineering strategies for precise, context-aware outputs, and understand how different technical approaches (e.g., inference with large language models, retrieval-augmented generation, fine-tuning) can enhance document quality and consistency. The course also covers data governance and the ethical use of AI within regulated industries, ensuring participants are prepared to integrate AI safely and responsibly into their documentation workflows.

The course will conclude with a breakout session in which participants can independently workshop a document of their choice with instructor consultation and support.

Learning Objectives

Identify opportunities to apply AI for developing food safety documentation, including SOPs, policies, and verification activities.
Use prompt engineering to guide AI-generated content for clarity, accuracy, and regulatory compliance.
Understand and compare technical approaches, such as large-language model inference and retrieval-based content generation.
Evaluate and refine AI-generated text to ensure precision and alignment with organizational standards.
Discuss ethical considerations and data governance principles in the use of AI for food safety applications.
Collaborate with IT, HR, and QA teams to integrate AI responsibly within existing documentation systems.
Use AI tools to draft and refine documents aligned with regulatory and organizational requirements.
Distinguish between traditional and AI-assisted documentation workflows.
Recognize potential biases, limitations, and compliance risks associated with AI-generated text.
Develop document templates or case studies during breakout sessions, applying techniques learned in the online modules.
Establish a framework for responsible AI use and document governance within their own operations.

Course Dates

January 26-27, 2026, 12 pm-4 pm, live via Zoom

Fee

$725 Flat Fee

Sample Agenda

Welcome, Introductions, Overview
• Determining what to document using AI
• Document development with AI assistance
AI in Food Safety
• Case studies describing AI applications to food safety
• Modeling approaches for AI
AI generation of videos for training tutorials
Approaches to AI Use in Document Development
Inference with a pre-trained Large Language Model (LLM)
Curation of a knowledge base for Retrieval-Augmented Generation (RAG)
Prompt Engineering
Breakout – Independent Work Developing First Draft
Manual Refinement and Review
Case Studies: Identifying Good and Bad Elements of Food Safety Documents
Breakout – Reviewing Each Other’s Documents and Report Out
Facilitators circulate (AS, CS, LQ, HS), Abby Snyder – report out and facilitated discussion
Ethics in AI Use for Food Safety Documentation
Breakout – Independent Work on Your Own SOP/Documentation Project

Abby Snyder

Associate Professor

Food Science

Abby Snyder

abs276 [at] cornell.edu

Alexander Solla

Executive Administrator

Dairy Foods Extension

Alexander Solla

(607) 255-3459
ahs24 [at] cornell.edu