2.3.1 Big Data and AI in the Food Supply Chain: A Game Changer

Big data refers to vast sets of structured and unstructured data generated at high velocity and volume. In the context of the food supply chain, big data plays a pivotal role in:

Market Analysis:

Consumer Insights: Big data analytics allows businesses to gain profound insights into consumer preferences, behaviors and trends, addressing the demand for "Taste, pleasure, fun."

Market Trends: By analyzing data from various sources, including social media, online reviews and sales records, businesses can stay ahead of evolving market trends.

Product Development:

Personalization: Big data enables personalized product recommendations and customization, aligning with the trend of addressing "Specific nutritional needs" and "Convenience."

Optimizing Recipes: Food companies can use data-driven insights to optimize recipes, ensuring the highest quality and taste.

Operational Efficiency:

Supply Chain Optimization: Through real-time monitoring and data analysis, companies can streamline supply chain operations, reducing waste and enhancing "Convenience."

Cost Reduction: Big data analytics helps identify cost-saving opportunities and ensures the affordability of products without compromising quality.

Source: Freepik Author of 3 graphics: storyse

Artificial Intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals. It is also the field of study in computer science that develops and studies intelligent machines. "AI" may also refer to the machines themselves.

AI makes big data analytics simpler by automating and enhancing data preparation, data visualization, predictive modeling and other complex analytical tasks that would otherwise be labor-intensive and time-consuming. As a result, it predicts and indicates potential threats, supports and facilitates the decision-making process.