NewN AI: "Rising Interest in Meal Plans and Recipes...Develops Food Ingredient Price Prediction Model"

NewN AI, a generative artificial intelligence (AI)-based big data analytics company, has developed a "food ingredient price prediction model" based on consumer perception data, establishing a technological foundation for proactively responding to fluctuations in food prices.

The food ingredient price prediction model was applied to the recently released "AI Report on Dietary and Major Food Ingredient Trend Changes." The model was designed using 67 million pieces of social media big data generated from blogs, online communities, X (formerly Twitter), knowledge-sharing platforms, and YouTube between January 2021 and June 2025, covering approximately five years.

According to the AI report, mentions related to dining out and food delivery have decreased over the past year, while searches for meal plans and recipes have surged, indicating a clear shift toward "self-planned diets." Consumers are moving away from "weight management"-focused diets and are actively seeking "health management diets" and "anti-aging diets" that consider health management, disease prevention, and nutritional balance.

This shift has also influenced major food ingredient consumption patterns. References to ingredients associated with antioxidants, blood sugar control, and gut health have increased, and there is growing interest in health-friendly ingredients such as plant-based proteins, complex carbohydrates, and natural sweeteners. The rise in recipe-related keywords like "low-sugar rice cooker," "even cooking," and "rich flavor" demonstrates that consumers prefer cooking methods that balance taste and health.

NewN AI believes that these consumer perception trends are closely linked to actual food ingredient demand and price fluctuations, which led to the development of the prediction model. The model uses the volume of consumer mentions of recipe ingredients as a core indicator and combines this with data on price indices, exchange rates, climate, and oil prices to calculate price volatility. With a prediction accuracy of over 80% for key categories such as vegetables, grains, and livestock products, the model is drawing attention for its potential application in procurement strategies within the distribution industry.

With data-driven predictions, food ingredient distribution companies can fine-tune their supply and demand planning. Food manufacturers can reduce production and inventory burdens. The expansion of food tech businesses, such as personalized meal subscription services and AI recipe recommendation platforms based on consumer data, is also expected to accelerate.

Bae Seonghwan, CEO of NewN AI, stated, "Dietary trends directly impact the food ingredient market. The most significant aspect of this model is its ability to accurately interpret changing consumer perceptions and apply them to price prediction." He added, "We plan to further advance the 'AI price prediction model' so that major distributors and food manufacturers can utilize it, thereby contributing to innovation in the food tech market."