Canada backs food processing AI and automation with C$50M investment

Canada is investing C$50 million (US$35.2 million) in the Canadian Food Innovation Network (CFIN) to help food and beverage processors adopt automation, artificial intelligence, and digital manufacturing, with smaller businesses a particular focus. 

Industry Minister Mélanie Joly announced the funding this week through the Strategic Response Fund and Canada’s National Food Security Strategy. The investment is intended to improve productivity, expand domestic processing capacity, and accelerate the commercialization of Canadian technologies. 

CFIN CEO Dana McCauley says processors are trying to contain prices while using “equipment and systems that haven’t kept pace with their global competitors.” Its Food 4.0 plan aims to address that gap by supporting Canadian technology suppliers and helping manufacturers adopt their tools. 

The industry-led nonprofit connects food businesses with expertise, partners, and technologies. With the additional funding, CFIN is expected to support more than 200 small and medium-sized enterprises and facilitate up to C$200 million (US$140.9 million) in follow-on investment. 

The announcement does not specify application dates, individual funding limits, or how much of the investment will go directly to companies. 

From funding to factory adoption 

Recent CFIN-backed projects illustrate the range of technologies moving toward commercial use. In August, the network awarded nearly C$747,000 (US$526,000) to eight projects through its Innovation Booster program, spanning AI applications, processing systems, and ingredient development. 

Recipients included CBS Bio Platforms, which is developing an enzyme-based process to turn canola meal into food-grade protein, and Bliq Photonics, which is bringing real-time optical sensing to chocolate production lines. Other projects address operational challenges in food processing and distribution using AI. The program supports smaller businesses with product development, technical hurdles, and market validation.CFIN-backed projects include an enzyme-based process to turn canola meal into food-grade protein. 

The focus on factory modernization echoes concerns raised in our May interview with Tetra Pak. Sean Sims, vice president of automation and solutions, said manufacturers face rising input costs and workforce pressures while operating systems that have evolved over decades. 

Sims advocated upgrading in stages, starting with the most pressing production problems. He pointed to Greek dairy producer Delta’s replacement of a 30-year-old automation system, covering milk reception, pasteurization, cleaning-in-place, and integration with yogurt production. According to Tetra Pak, the upgrade reduced manual intervention and improved product consistency. 

He also highlighted digital twins, which let manufacturers simulate changes to production lines, optimize recipes, and test improvements without disrupting operations or wasting product. Sims said connected, reliable data and workforce training would be essential for companies to turn those capabilities into measurable gains. 

Data and skills gaps slow AI adoption 

For ingredient developers, AI adoption also raises questions about the data and skills needed to make the technology useful. In a February interview on AI in food development, the Institute of Food Technologists’ president, Peggy Poole, said AI could help developers assess formulation changes across multiple product attributes and narrow ingredient and processing options before trials. 

However, she identified gaps in employee training and the ability to move reliable data between teams and systems. Poorly connected or misreported data, she warned, limit the value of AI insights.