Artificial Intelligence in Food
Quality Control Training
11 – 15 May 2026
Sandton Centre
Johannesburg South Africa
Register Now! Limited Seats Available!
R19,999.00 Per Delegate
Course Introduction:
The food industry is rapidly adopting Artificial Intelligence (AI) to enhance quality control, safety, efficiency, and traceability. This training equips participants with the knowledge and practical skills to implement AI-driven tools for detecting defects, predicting product quality, automating inspection, and complying with regulatory standards. Through real-world case studies, interactive sessions, and hands-on demonstrations, participants will gain the confidence to apply AI technologies within food production environments.
Course Objectives:
By the end of this course, participants will be able to:
• Understand the role of AI and machine learning in food quality assurance.
• Identify key AI tools for food defect detection, grading, and safety monitoring.
• Apply predictive analytics to improve product consistency and reduce waste.
• Integrate AI with existing food safety management systems (HACCP, ISO 22000).
• Evaluate and select suitable AI solutions for specific production processes.
• Ensure compliance with food quality regulations when using AI-driven systems.
Who Should Attend:
This course is ideal for:
• Quality Assurance (QA) & Quality Control (QC) Managers
• Food Production Supervisors & Technologists
• Food Safety Auditors & Inspectors
• Research & Development (R&D) Professionals
• Data Analysts & AI Specialists in the food sector
• Regulatory and Compliance Officers
• Food Processing Engineers
Course Outline:
Day 1 – Introduction to AI in the Food Industry
• Overview of AI and machine learning concepts
• Evolution of AI in food processing & quality control
• Current trends and case studies in AI applications
• Understanding image recognition, predictive analytics, and automation in food quality
• Opportunities and challenges of adopting AI
Day 2 – AI Tools for Food Quality & Safety
• AI-powered vision systems for defect detection
• Machine learning for grading and sorting
• AI in food freshness monitoring and shelf-life prediction
• Sensor integration with AI platforms
• Demonstration: Automated quality inspection workflow
Day 3 – Data Management & Predictive Analytics
• Data collection, labeling, and preparation for AI models
• Building predictive models for quality control
• AI for process optimization and waste reduction
• Introduction to cloud-based AI platforms for the food industry
• Case study: Reducing defects through AI-driven analytics
Day 4 – Integrating AI with Food Safety Standards
• AI in HACCP monitoring and ISO 22000 compliance
• Traceability systems enhanced with AI & blockchain
• AI for allergen detection and contamination prevention
• Regulatory considerations for AI implementation
• Group exercise: Designing an AI-supported quality control plan
Day 5 – Practical Applications & Future Trends
• Hands-on session: AI image recognition for product inspection
• Emerging AI technologies for food quality
• Sustainability and environmental impact of AI adoption
• Developing an AI implementation roadmap for your organization
• Final Q&A, review, and certification ceremony
End of the workshop
IN HOUSE AND ONLINE TRAINING
While both In-House and Online training can present with cost-effectiveness and time-efficacy, there are some very specific differences between in-house courses and those based online.
The demand for additional courses by individuals or groups of people is increasing. Still, it depends entirely on the preferences of a person what type of training he or she wants to receive. Online courses and in-house training carry some similarities but they are considered to exhibit some very pivotal differences too. Despite that, both types of learning can be really beneficial for attendees.
For Registration and other Training arrangements,
contact us on the detail below.
SOUTH AFRICA : +27 11 057 6001
TANZANIA Cell: +255 769 688 544
WhatsApp +27 79 574 0389
info@bmktraining.co.za / www.bmktraining.com
