Introduction
The fresh food industry has enjoyed a stable environment all these years but is now facing a dynamic competitive environment due to changes in buying preferences of customers, challenges with transport, product handling and processing and increased costs which put pressure on the already notoriously thin margins. This is where Artificial Intelligence (AI) comes to the rescue. Food supply chains face increased consumer demands for food quality and sustainability.
Before delving deeper into how artificial intelligence optimizes the food supply chain, let’s first understand the terms supply chain and AI.
What Is Supply Chain?
Supply chain refers to a network comprising of individuals, technologies, resources, activities, and organizations which are involved from the creation until the sale of a product. It includes the delivery of source materials from the supplier to the manufacturer until the eventual delivery to the end user. Supply chain management refers to the integration and coordination of the three main flows of the supply chain which are the information flow, product flow, and finances flow.
Understanding the concept of Artificial Intelligence (AI)
Artificial Intelligence is that area of computer science which deals with the creation of intelligent machines which think, react, and work like humans. It refers to the simulation of human intelligence processes using computer systems. These processes include learning, reasoning, and self-correction. AI is utilized across various industries such as manufacturing, healthcare, law, finance, education, and business.
Role of AI in optimizing the food supply chain
1. Machine learning for supply chain planning
Machine learning is an application of AI based on the fact that machines must be given access to data thereby making them learn by themselves. Supply chain planning is a crucial activity in supply chain management. In today’s business scenario, intelligent work tools are a must as they help build concrete plans.
Machine learning supports the supply chain in the following ways:
- Forecasting demand, supply, and inventory.
- SCM professionals can provide scenarios based on intelligent algorithms.
- Optimizing delivery of goods.
- Balancing supply and demand.
- Setting action goals for measuring parameters of success.
2. Warehouse management
The success of supply chain planning depends a great deal on proper warehouse and inventory-based management. Flaws in supply can prove to be a disaster for any consumer-based retailer or company. A forecasting engine with artificial intelligence reviews the various combinations of algorithms and data streams for having the most predictive power for the various forecasting hierarchies. AI offers an endless loop of forecasting with a constantly self-improving output.
3. Chatbots for operational procurement
To streamline procurement through augmentation and automation of chatbot capability requires access to robust and intelligent datasets. ‘Procuebot’ can be accessed as a frame of reference. It signifies the brain of the machine.
Chatbots can be used in the following ways to streamline operational procurement:
- Placing purchase requests.
- Setting and sending actions to suppliers regarding compliance materials and governance.
- Documenting, filing, and receiving order requests, invoices, payments.
- Answering internal questions with regard to procurement functionalities.
- Having conversations with suppliers.
4. Data cleansing and enhancing data robustness
Natural Language Processing (NLP) is an element of machine learning and AI. It has staggering potential to decipher large amounts of streamlined foreign language data. NLP will help build data sets regarding suppliers and decipher untapped information due to language barriers. From a CSR and governance perspective, it can aid in streamlining auditing and compliance actions which were previously unavailable because of language barriers between buyers and suppliers.
5. Optimizing logistics
AI exhibits great potential in logistics optimization. Using driverless vehicles can help reduce human labor costs, add elements of environment-friendly operations, and reduce lead times. These vehicles will be efficient and accurate than humans. Tesla, the American automotive and energy company, plans to release an electric semi truck with driverless ability. Following the development, this has the potential to revolutionize transportation in the supply chain.
Conclusion
Comprehensive and reliable communication is highly relevant in food supply chains for quality management, quality assurance, and sustainable competitive advantages. But, owing to agency issues, these cannot always be taken for granted. Regulations by private and government agencies offer intensive focus to the quality-related information stored on the food supply chains.
Suppliers and retailers are now increasingly turning to technology to reduce waste and improve inventory management. When it comes to improving the visibility and management of the food supply chain, AI proves to be the best solution as it optimizes the reduction of waste and improves the freshness of the product.
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