By Sukanya Ganesh in AI — Nov 11, 2024

AI-Powered Food Labeling

AI is transforming food labeling by ensuring accuracy, regulatory compliance, and transparency, fostering greater consumer trust and confidence in product information.

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How AI is helping in food labeling and claims

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AI is transforming food labeling verification, ensuring that health claims, ingredient lists, and other details are accurate, compliant, and transparent for consumers. Using technologies like Natural Language Processing, machine learning, and image recognition, AI can cross-check labels against regulatory guidelines, confirm claims like "organic" or "gluten-free," detect allergens, and flag misleading information. This automation improves labeling accuracy and boosts consumer trust by keeping food products compliant with evolving regulations.

Nestlé

Nestlé, one of the world’s largest food and beverage companies, uses AI to ensure that their product labels are accurate and compliant with local regulations across different markets. By applying Natural Language Processing (NLP):

Nestlé uses AI tools to scan labels for claims such as "organic," "natural," or "high in protein" and check if they comply with regulatory requirements in each country.
For example, in the U.S., Nestlé products claiming to be “organic” must comply with USDA organic regulations. AI ensures the product ingredients and sourcing meet the USDA's definitions of "organic."
This helps ensure that different labels across markets align with local laws, reducing the risk of misleading claims or fines.

Coca-Cola

Coca-Cola, through its participation in the SmartLabel initiative, uses AI to help consumers easily access detailed information about ingredients, allergens, and nutrition facts by scanning a QR code. Coca-Cola’s products feature:

AI-powered ingredient databases that cross-reference information from official regulatory sources (FDA, USDA) to make sure what’s listed on the label is correct and complete.
The system can flag any potential issues such as undisclosed allergens or prohibited ingredients.

For example, a product like Coca-Cola Zero Sugar, when scanned through the SmartLabel system, will show not only ingredients but also their regulatory compliance, ensuring no harmful ingredients are being used.

Walmart

Walmart uses AI-based image recognition tools to automatically check product labels on items sold in their stores and on their website. This includes verifying that the placement of nutrition facts, expiration dates, and ingredient lists meet FDA labeling standards.

Walmart’s AI can scan thousands of labels to ensure that information is displayed correctly, with the proper font size and prominence, especially for allergens like nuts or soy.
For example, if a peanut butter product's label doesn’t clearly highlight the allergen warning, Walmart’s system would flag it and request corrective action from the supplier.

Unilever

Unilever, which owns brands like Ben & Jerry’s, Dove, and Hellmann’s, uses AI to verify the health claims made on their product packaging. They apply machine learning models that analyze claims like "low cholesterol" or "good for heart health" by cross-referencing them with scientific studies and regulatory databases.

For instance, if a product like Hellmann’s Light Mayonnaise claims to be "low-fat," the AI system can check regulatory thresholds for "low-fat" food in the region (like FDA guidelines in the U.S. or EFSA guidelines in Europe) and ensure compliance.
If a claim cannot be substantiated with approved research or doesn’t meet the regulatory definition, it is flagged for review before the product reaches the market.

By applying AI across these different functions, the accuracy of food labeling improves, reducing the risk of regulatory violations and ensuring that consumers have access to clear, truthful, and non-misleading information.