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Maple Leaf Foods 14th Annual Food Safety Symposium Highlights AI's Role as a Catalyst in Transforming Food Safety

Hosted its 14th annual Food Safety Symposium as part of the company's commitment to providing safe food for all Canadians and foster knowledge sharing among experts within the food industry. The symposium gathered industry leaders and experts to discuss the transformative role of Artificial Intelligence (AI) in advancing food safety.

"AI and food safety are deeply intertwined, with AI transforming our business in ways we are only beginning to understand," said Curtis Frank, President and CEO, Maple Leaf Foods. "Our deep commitment to food safety is rooted in our past and in our everyday promises in how we hold ourselves accountable and continue to set the highest standards. We must continuously advance our efforts to deliver safe, nutritious food and use AI to build a safer, more sustainable food system."

Keynote speaker, Nihar Dalmia, Partner, Omnia AI, Deloitte, spoke about the evolution of AI, emphasizing the pivotal moment we're at with AI in the food industry. "We're on the cusp of an AI revolution: we've moved from AI being tools for scientists and large corporations to now being for all of us. It's critical to understand the potential of AI and how to drive tangible business value," said Dalmia. "Looking ahead, we see trends like smart packaging, AI-powered robotics, and personalized food safety solutions shaping the industry. What comes next, as organizations scale AI initiatives, is navigating the technological change and enabling AI agents to shape organizations with comprehensive, responsible AI practices."

The Symposium featured a panel discussion with Conor Cahil, Head of Science & Innovation, Dawn Farms Foods and Dr. James Doyle, Director of Global Accounts, Crème Global, which emphasized the importance of precise data acquisition, optimizing processes, and how AI enhances long-term sustainability and consumer safety. Case study examples presented by Dawn Farms Foods highlighted their forensic approach to food safety that uses AI to enhance labelling controls, quality monitoring, intuitive training, and predictive detection.

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