Freshness Prediction Artificial Intelligence (AI) Market Report 2026

The freshness prediction artificial intelligence (AI) market size has grown rapidly in recent years. It will grow from $1.83 billion in 2025 to $2.19 billion in 2026 at a compound annual growth rate (CAGR) of 19.6%. The growth in the historic period can be attributed to rising concerns over food waste reduction, growth in perishable goods trade, increasing adoption of cold chain logistics, expansion of retail and grocery chains, demand for improved inventory management efficiency.

The freshness prediction artificial intelligence (AI) market size is expected to see rapid growth in the next few years. It will grow to $4.52 billion by 2030 at a compound annual growth rate (CAGR) of 19.9%. The growth in the forecast period can be attributed to increasing demand for real-time predictive analytics, growth in smart supply chain solutions, rising focus on sustainability in food systems, integration of ai-driven quality assessment tools, expansion of automated inventory and logistics systems. Major trends in the forecast period include increasing adoption of real-time shelf life prediction solutions, growing use of data-driven inventory optimization strategies, rising demand for food waste reduction technologies, expansion of predictive quality monitoring across supply chains, increasing integration of freshness prediction in retail operations.

The growing initiatives to reduce food waste are expected to drive the expansion of the freshness prediction artificial intelligence (AI) market going forward. Food waste reduction initiatives refer to planned actions and measures implemented by governments, businesses, and organizations to minimize food wastage, enhance resource efficiency, and improve sustainability throughout the food supply chain. The increase in food waste reduction initiatives is driven by rising environmental concerns, as reducing food waste helps decrease greenhouse gas emissions, conserve resources, and lessen overall environmental impact. Freshness prediction artificial intelligence (AI) contributes to food waste reduction efforts by analyzing real-time data such as temperature, humidity, and product conditions to accurately estimate shelf life, enabling better inventory management, timely distribution, and reduced spoilage across the supply chain. For example, in January 2026, the United States Environmental Protection Agency stated that the U.S. government has established a target to cut food waste in retail, food service, and residential sectors by 50% by 2030, with annual investments of $14 billion in cost-effective solutions expected to reduce 45 million tons of food waste each year. Therefore, the increasing initiatives to reduce food waste are driving the growth of the freshness prediction artificial intelligence (AI) market.

Leading companies operating in the freshness prediction artificial intelligence (AI) market are focusing on developing advanced solutions, such as integrated AI-driven fresh operations platforms, to improve freshness prediction accuracy, optimize perishable inventory decisions, and reduce food waste across retail supply chains. Integrated AI-driven fresh operations platforms refer to centralized digital solutions that use artificial intelligence to optimize fresh food inventory, demand forecasting, and shelf-life management in real time, thereby reducing waste and improving supply chain efficiency. For example, in September 2025, Afresh Technologies, a US-based freshness optimization AI company, launched the Fresh Store Suite, an AI-powered platform that integrates inventory management, demand forecasting, ordering, and production planning into a unified freshness optimization system across fresh departments. The platform enables grocers to make faster, data-driven decisions, reduce food waste, and improve product freshness through predictive replenishment and cross-department AI optimization while streamlining fresh operations and enhancing profitability.

In March 2025, Crisp Inc., a US-based retail AI platform, acquired Shelf Engine Inc. for an undisclosed amount. Through this acquisition, Crisp aims to utilize Shelf Engine’s AI technology to enhance retail demand forecasting, improve inventory management, and increase operational efficiency across its retail and food distribution networks. Shelf Engine Inc. is a US-based technology company that uses Freshness Prediction AI to optimize inventory and minimize waste for perishable goods.

Major companies operating in the freshness prediction artificial intelligence (AI) market are Google LLC, Microsoft Corporation, Cargill Incorporated, Amazon Web Services Inc., Siemens AG, IBM Corporation, Oracle Corporation, SAP SE, TOMRA Systems ASA, Leanpath Inc., Afresh Technologies Inc., Intello Labs Private Limited, Winnow Solutions Limited, Clarifruit Ltd., OneThird B.V., AgShift Inc., Strella Biotechnology Inc., Wasteless Ltd., OpSense Ltd., Kitro SA.

North America was the largest region in the freshness prediction artificial intelligence (AI) market in 2025. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the freshness prediction artificial intelligence (AI) market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the freshness prediction artificial intelligence (AI) market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Taiwan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The freshness prediction artificial intelligence (AI) market consists of revenues earned by entities by providing services such as food freshness detection, shelf life prediction, spoilage risk assessment, quality grading automation, real-time freshness monitoring, supply chain optimization, storage condition analysis, predictive inventory management, waste reduction analytics, and automated quality inspection. The market value includes the value of related goods sold by the service provider or included within the service offering. The freshness prediction artificial intelligence (AI) market includes sales of computer vision-based models, machine learning prediction models, sensor-based prediction systems, cloud-based freshness prediction systems, edge artificial intelligence systems, and multimodal artificial intelligence models. Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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