These days, it’s nearly impossible to read or hear about optimization in pet food — whether it’s for an entire business or a focused area — without encountering two specific letters: AI.
Many companies in the industry, from manufacturers to suppliers to agencies, are using AI in myriad ways: “smart” packaging, formulation, product development, processing, marketing, consumer data analysis, supplier auditing, pricing and market forecast demand, palatability, even as a “personal assistant” for any of these tasks.
Yet, is AI omnipresent in pet food? According to a mid-2025 poll on PetfoodIndustry.com, only 36% of respondents reported active AI usage, while 26% said their companies were not using any AI tools and another 26% were unsure. “An additional 12% indicated they are evaluating AI tools but have not yet moved to implementation, suggesting the adoption numbers may increase in the coming months,” reported Lisa Cleaver.
Pet food is not alone in being slow to try AI. In human food, 36% of companies surveyed by TraceGains, also in mid-2025, reported they are not using AI at all, even higher than in pet food. A TraceGains executive called it “the majority of brands still operating in the stone ages.”
As with the advent of any new, disruptive technology or phenomenon, good reasons exist for resistance. In the PetfoodIndustry.com poll, nearly 25% of respondents identified lack of expertise or insufficient technical knowledge as their primary challenge, far outpacing other barriers.
At the American Feed Industry Association’s (AFIA) Pet Food Conference during IPPE 2026, a panel of AI experts addressed other concerns, including a misconception that companies need perfect data to implement AI, fear that AI will replace jobs and lack of trust and accuracy. And yes, AI is infamous for making stuff up! It also inspires legitimate anxiety over what its growth means for humans. I’ve experienced both myself, as I (like many of my colleagues) have experimented with AI for specific tasks within strict guidelines.
The AFIA panel recommended pet food experimentation through “low-risk applications like summarizing reports, generating content ideas, analyzing consumer sentiment from reviews or identifying patterns in product feedback,” Cleaver wrote. “These applications help teams become familiar with AI capabilities before tackling more complex manufacturing or formulation challenges.”
As AI becomes more powerful and ubiquitous, no one really knows where it will lead. For now, with careful application, it seems to offer pet food companies and professionals another suite of tools to explore improving processes, work and products.
