Trusted Artificial Intelligence to Transform Agriculture and Food Sector

We aim to evaluate the immense potential data and AI technologies offer to shape the future of agriculture and food and create strategies and solutions to elevate food production to become more resilient and sustainable.

data
ecosystem
data ecosystem
application ecosystem
responsible AI innovation
AI technologies
innovation in agriculture

Responsible Innovation for Agriculture and Food

food safety

Improving Food Production and Safety

Driving Sustainable Growth in AgriFood

Improving Animal and Human Health

Redefining Farming for
the Future

Smart Retail and Supply Chain Resilience

improving resilience

Our Mission

AI4Food’s mandate is to contribute to the creation of new knowledge and innovation aimed at enhancing the resilience, safety, production, and sustainability of agriculture and food systems, both nationally and internationally, through the use of data and AI technologies, digital infrastructures, new policies, and advanced business strategies.

responsible development

Focus Areas

Artificial Intelligence for Food (AI4Food) seeks to pioneer research and learning at the intersection of responsible data technologies and Artificial Intelligence (AI) in  agricultural and food systems.

AI4Food is not only aimed to drive innovation but also address the broader regional and multi-jurisdictional strategies for responsible innovation, use, and integration of these technologies in real-world applications and scenarios  in agri-food.

1

Application Ecosystem

Smart farming
Food sustainability
Food waste management
Climate smart
Food supply chain resilience
Food integrity
Smart food retail
Consumer behaviour
Livestock and human health
Food traceability and transparency

2

Responsible Artificial Intelligence Innovation

Legal and standards
Regulation and Policy
Social
Human Aspect
Sustainability
Trustworthiness
Governance
Data
Economical impact
Business model

3

Artificial Intelligence Technologies

Digital Twins
Distributed AI
Automation and Robotic
Decision Support Systems
Human-centric AI
Data

4

Data Ecosystem

Analytics
Interoperability
Data integration
Data processing
Legal and standards