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The potential of AI in the agribusiness sector towards a global perspective in terms of sustainability
The potential of AI in the agribusiness sector towards a global perspective in terms of sustainability



07 September 2021

The potential of AI in the agribusiness sector towards a global perspective in terms of sustainability

Less waste, greater efficiency, more sustainability, and transparency with respect to food safety: these are the five pillars recently shared by all food industries.

The growing population is leading to “undernourishment”.


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According to the Food and Agriculture Organization (FAO)[1], one in every nine people in the world lacks food for leading their daily life. This means that food supply is in high demand by 70% worldwide and nearly will double in developing countries.

Supply chain optimization through artificial intelligence in agribusiness


This obviously means that more food and beverage are required to feed an ever-growing world. In consequence, large and well-organized agriculture farms, food processing manufactures, and restaurant businesses are stressed to optimize better their offerings from one side, whereas governments are doing a lot of initiatives and incentives from culture-awareness to financial and employment support, such as India, where even new regulations for the agrochemicals and agri-food projects are ongoing in the most diversified country for agriculture with 14 different climates and very large crops.


Less waste, greater efficiency, more sustainability, and transparency with food safety compliance as strictly required by FSMA (Food Safety Modernization Act) are the 5 pillars that almost recently all food industries are agreeing on as a strategy and vision.

All consumers and stakeholders in the global supply chain need to have transparent information concerning the path of food from farm to fork. With such an increasing need for transparency and the new food safety regulations on good hygiene practices for the employees and machines to avoid contamination and foodborne illnesses, supply chain management becomes a top priority.


The possibility of using Fourth Industrial Revolution [4.0 IR] technologies such as Artificial Intelligence, machine/deep learning, and computer vision robotics as a key for sustainable food production had been proposed and implemented by many so far, such as Kraft Heinz.

Its vision for AI-delivered insights is more related to automation, where predictive/condition-based maintenance with sensors connected to mounted plates on the production lines that measure any vibration and send data to a software to analyze and predict whether a unit is potentially going to fail. Therefore, it can be adjusted before to avoid any unplanned downtime, extremely expensive for the company if not done during the normal maintenance shift.

Another pragmatic approach had been taken by Carlsberg to help consumers in getting fast automatic insights from a mobile AI-enabled app about the beer constituents and its safety.  Other use cases and solutions leveraging AI technologies are related to waste management with optical sorting sensors and hyperspectral cameras to sort fresh products by size, color, and foreign matters before developing the finished packs and reaching consumers or retailers to be discarded then. Potatoes can be sorted either to make chips, packed fresh or mashed in containers.


The United States Department of Agriculture[2] claims that: “In the United States, food waste is estimated at between 30-40 percent of the food supply. During the 2019-2024 period, the Food and Beverage market is expected to register a CAGR of over 65.3%”. According to McKinsey & Co[3], Artificial Intelligence can solve this problem and unlock a $127 billion opportunity by reducing food waste in 2030. Based on Technavio[4], the market of AI-driven food industry is projected to reach 332.58 million USD by 2021, with a CAGR of over 42%. Technavio forecasts that by the end of 2019, robot implementation in the food industry will be up to 30% with respect to Food Safety standards.


So, investing in AI technologies for Food companies is incredibly great if we look at the size of the investment with the potential size of the pay-off. For instance, not only does AI help companies with critical tasks such as quality control and demand planning, but it is also being used in functions such as new products development, supply chain optimization, cleaning processing equipment without disassembling, checking personnel hygiene, predictive maintenance, remote monitoring, and precision agriculture by growing better food. All are already implemented by different companies and smart farms.

For example, AI is used to monitor the effects of variables like UV light, salinity, heat, and water stress on seeds/plants. AI in agriculture, namely next-generation farming, had been analyzed by Cognilytica[5], declaring that: 75 million IoT sensored devices are installed in farms by 2020 for: detecting plants disease and pest control, boosting crop yields selection, and improve soil health with smart irrigation and right bio-pesticides, seasonal forecasting, chatbots to support farmers and agricultural robots for collecting fruits at the right timing. The grocery and restaurants industry is also using AI to target customers with personalized offers/menus, manage inventory, and reduce waste. For example, Wellio[6] uses machine learning and behavioral science to provide personalized recipe recommendations with online shopping, whereas Habit develops personalized nutrition plans adapted to the diet style or nutrition test.


As you can realize, the benefits of AI in the next generation of agriculture and food and beverage industries are more than being summarized as below:

  1. Optimization in supply chain management through logistics and predictive analytics with more transparency from farm to consumer
  2. Digitalization of the supply chain to drive more revenue and a better understanding of the situation beyond human capability
  3. Reduction of time to market with new products development and better deal with uncertainties with more accurate forecasting to manage pricing and inventory
  4. Automation in cleaning, collecting, sorting, and many other tasks that reduce labor costs, increase the speed of the process, and improve the quality of yields.
  5. Compliance to safety standards by monitoring and testing product at every step of the supply chain

In conclusion, the implementation of AI and ML in food manufacturing and restaurant businesses is already moving the industry to a new level, enabling fewer human errors and less waste of abundant products; lowering costs for storage/delivery and transportation, and creating happier customers, quicker service, voice searching, and more personalized orders.

Employing sustainable fourth industrial revolution (Industry 4.0) technologies in Agri-Food and Beverage sectors can feed any creature with the necessary food supply by 2050 in an eco-friendly manner. Robotics is still young introduced, even for big factories and restaurant businesses, but it will occupy its niche very soon, bringing an important benefit in the long term. These are only a few of the applications of AI in the food industry, and we expect to see many more as the technology is advancing.

Stay Tuned!








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