The Role of AI in Communication Between the Pet Food Industry and Consumers

The constant expansion of the pet food market demands solutions that integrate innovation, quality, nutrition, and sustainability while offering transparency. Artificial intelligence, already used in health and agriculture, is now gaining ground in animal nutrition. In the pet food sector, AI contributes to the development of more precise diets and the optimization of production processes and the supply chain as well.

In this context, AI serves as a strategic tool to bring the industry and consumer together through digital solutions that strengthen loyalty and sales experience. Communication between brands and pet parents—once limited by traditional advertising—is now driven by intelligent systems that provide recommendations, real-time support, and preference analysis. This shift represents a new era for the industry and its customers, benefiting both sides.

It also helps the industry to keep up with market demands. Companies gain an advantage by quickly identifying trends through data, social media comments, and purchasing preferences.

Artificial intelligence serves as a strategic pillar for the future of the pet food industry. More than just technology, it is an ally that ensures quality, innovation, sustainability, and personalization in this continuously evolving and demanding sector.

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Technological Advancements Improving the Quality of Pet Food

Josiane Volpato

Application of AI Related to Tutors

Artificial intelligence strengthens the relationship between the industry and consumers by offering tools that guide them on the ideal pet diet. AI chatbots allow tutors to access information without human contact. These systems answer ingredient questions, indicate foods tailored to age, weight, and size; they also remind tutors to restock food. Continuous assistance promotes benefits and security.

In e-commerce and apps, AI recommends products based on a pet's profile and the sales record. It reduces indecision when faced with available options and improves precision in selecting the proper diet.

AI tools can process thousands of comments and analyses on digital platforms, identifying patterns of preference or dissatisfaction. These insights help the industry understand tutors' demands, anticipate consumption trends, and adjust products or marketing strategies. Technical language is an obstacle in formulation; AI acts as a 'translator' by explaining how ingredients function. In this way, tutors understand that fibers and antioxidants play a functional role in animal well-being—they are not simply a 'filler.'

Using AI is beneficial for both the industry and customers. On one hand, companies gain loyalty, better marketing precision, and market-aligned products. On the other hand, tutors are more confident, with better benefits and security when selecting food, besides personalized pet care.

AI is redefining the relationship between pet parents and the pet food industry. Offering intelligent assistant tools, personal recommendations, feedback analysis, and clear communication, AI strengthens loyalty, improves the consumption experience, and attracts brands and consumers. This movement not only represents technological innovation but also a strategy to address an increasingly demanding market, focused on personalization.

 

By Josiane Volpato and Karla Memare
Source: All Pet Food Magazine


References
BSM PARTNERS. Understanding the Role of AI in Pet Nutrition: How Technology Is Shaping the Future of Pet Food. 2024. Disponível em: https://bsmpartners.net/insights/understanding-the-role-of-ai-in-pet-nutrition-how-technology-is-shaping-the-future-of-pet-food/

Garcia, R. G., Naas, I. A., Burbarelli, M. F. C., Caldara, F. R., Komiyama, C. M., Valentim, J. K., & Sgaviolo, S. (2025). Aplicações de inteligência artificial para otimização do bem-estar e sustentabilidade em sistemas de produção animal. In Nutrição animal: Novas perspectivas e avanços para a sustentabilidade e otimização dos sistemas de criação - Vol. 2 (pp. 8–34). Editora Científica. https://doi.org/10.37885/250619568
KLEIN, Katharina; MARTÍNEZ, Luis F. O impacto da antropomorfização na satisfação do cliente no comércio eletrônico: um estudo experimental no setor alimentício. Electronic Commerce Research, 16 maio 2022. DOI: https://doi.org/10.1007/s10660-022-09562-8. Disponível em: https://pmc.ncbi.nlm.nih.gov/articles/PMC9108695/. Acesso em: 4 set. 2025.
TYLER, J. Donos de animais de estimação mais jovens estão mais interessados em ração personalizada para cães. Pet Food Processing, 26 ago. 2021. Disponível em: https://www.petfoodprocessing.net/articles/15034-younger-pet-owners-more-interested-in-personalized-dog-food. Acesso em: 04 set. 2025.
Petfood Forum News. AI in pet food marketing: Strategies, challenges and future trends. Publicado em 6 de março de 2025. Disponível em: https://www.petfoodindustry.com/news-newsletters/petfood-forum-news/article/15739303/ai-in-pet-food-marketing-strategies-challenges-and-future-trends

Petfood Industry. (2025). Pet food industry split on AI adoption; marketing emerges as top priority. Retrieved September 4, 2025, from https://www.petfoodindustry.com/pet-food-market/article/15753686/pet-food-industry-split-on-ai-adoption-marketing-emerges-as-top-priority

SUDERSANADAS, Kavita. Application of artificial intelligence on nutrition assessment and management. European Journal of pharmaceutical and medical research, v. 8, n. 6, p. 170-174, 2021.

TEDESCHI, Luis O. ASAS-NANP Symposium: Mathematical Modeling in Animal Nutrition: The progression of data analytics and artificial intelligence in support of sustainable development in animal science. Journal of Animal Science, v. 100, n. 6, p. skac111, 2022.

SIAD, Oussama; BOUZID, Chaima. Biotech meets Artificial Intelligence to Enhance the Value of By-Products in Animal Nutrition. Biological Sciences, v. 3, n. 1, p. 353- 365, 2023.

YANG, Zhongqi; KHATIBI, Elahe; NAGESH, Nitish; ABBASIAN, Mahyar; AZIMI, Iman; JAIN, Ramesh; RAHMANI, Amir M. ChatDiet: Empowering Personalized Nutrition-Oriented Food Recommender Chatbots through an LLM-Augmented Framework. arXiv, 18 fev. 2024. Disponível em: https://arxiv.org/abs/2403.00781

Zhang, L., Guo, W., Lv, C., Guo, M., Yang, M., Fu, Q., & Liu, X. 2023. Avanços na tecnologia de inteligência artificial para melhorar o bem-estar animal: aplicações atuais e progresso da pesquisa. An. Res. One Health. 2(1):93–109. https://doi.org/10.1002/aro2.44