Artificial Intelligence or AI is a technology that has allowed several machines and systems to inculcate some form of human intelligence as well as their behavior. AI has always been driven by systems that deploy the use of some sort of intelligent agents along with some complex algorithms for processing information, performing specific tasks as well as adapting to the dynamically changing inputs and environments.
Typical usage of AI involves human reasoning as
a model to make certain decisions backed by a vision of providing improved
insights, products, services and efficiencies. Talking about the supply chain,
AI acts as a catalyst and has several applications such as- information
extraction, analysis of data, planning of supply and demand, autonomous
vehicles, along with warehouse management.
Applications of AI Within Supply Chain Management
- Using Chatbots for Procuring Operations
Streamlining of procurement-related tasks with the help of an automated and augmented chatbot needs access to robust and smart data sets. Talking about the daily functions present in the supply chain, a chatbot can be used for the following set of tasks-
i. Conversing with suppliers at the time of trivial conversations
ii. Alerting suppliers in terms of governance and compliance materials
iii. Placing purchasing orders
iv. Answering internal questions related to procurement functions
v. Receiving, filing and documenting invoices and payments as well as order requests
Supply chain planning plays a crucial role in a supply chain management strategy. With the help of smart tools to build firm and robust business plans is now becoming inevitable in the modern-day business domain.
Machine Learning, when applied with supply chain planning, can be used for forecasting the inventory, demand as well as supply. The correct usage of Machine Learning with supply chain management tools can be extremely beneficial for revolutionizing the agility as well as optimizing the decision-making in the supply chain. The deployment of Machine Learning technology by the SCM experts can result in best outputs that are based on intelligent algorithms and machine analysis for big data sets. Such capability of Machine Learning can be used for optimizing the goods delivery and balancing supply and demand without any need for human review.
- Managing Logistics with Predictive Analysis
In today’s time, companies have been following a proactive approach as the predictive analysis is being used for forecasting information regarding customer trends as well as demand. With a future analysis regarding supply and demand helps the SCM system with strategic planning, procuring raw materials, controlling inventory, developing newer products and also carrying out supply analyses about the finished goods.
- Managing Inventory
In any SCM, the most significant task is the inventory assortment and is crucial as the information about stock availability is maintained based on the inventory that has been assorted. The assorting process is a time consuming one and is always prone to human errors. However, if the automated robots are deployed, then it can result in high accuracy for providing accurate inventory information and ultimately reducing the cost of the supply chain as well as human errors.
- AI in Logistics for Predicting Demand
AI can be extremely beneficial for enhancing supply chain processes. It can be used for improving demand and enhancing forecasting demand. Based on past experience and learning, one can get a complete analysis of the factors that hold an influence when it comes to catering to the demands of the market. Based on this, the supplier can make the best business decision.
- Optimizing Logistics Route
AI can be used for deciding the best route available to reduce shipping costs and making the shipping process faster. This can be extremely beneficial for the suppliers that own large e-commerce with a vast customer base. For such companies, AI can be a helpful technology as it can analyze the existing routes and perform the optimizing of route tracking.
- Predicting Peak Hours in Logistics Center
Today, in most of the logistics center, AI is being used with Machine Learning to monitor and predict traffic along with other factors that can have an impact on the shipping time for a consignment. Peak hours at the logistics center is essential when it comes to shipping. Thus, AI can be effectively used for predicting and avoiding such peak hours at the logistics center.
- Automated Quality Checking
When the quality checks are done automatically, it proves to be more advantageous as compared to manual methods that are deployed. Having an automated quality inspection backed by computer vision programs and machine learning algorithms helps in scanning the product in all the possible dimensions. When the product is scanned across all the axes, faults can be detected at nearly 1/4th rate as compared to a human performing the inspection process.
Significance of AI with Supply Chain
Artificial intelligence offers several benefits when It comes to SCM.
Some of these include-
- Data analysis, as well as insights, helps in creating actionable business intelligence that fuels continual enhancement
- Speed gets enhanced in the entire supply chain because of an efficient supply and demand planning that is powered by marketplace factors, consumer needs as well as other changes taking place in the environment
- Logistics get improved as there are optimized warehouse operations as well as distributions
- Costs get reduced due to savings in reduced inventory and storage-related costs. The goods are processed faster and gets distributed at much quicker rates
Challenges of Using AI in Supply Chain
Despite having the advantages mentioned above several applications, there are certain roadblocks when it comes to using AI in SCM.
Some of the potential challenges include-
- Updated and accurate data is necessary to gain essential to gain useful insights out of any AI-based system. Thus, Ai systems need to be integrated with systems and databases for accessing, cleansing and analyzing the data
- AI is dependent on algorithms and models for gaining insights and actions throughout the entire supply chain. SCM needs to have period checks deployed against these models to ensure that everything is compliant and working within the defined parameters
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AI should never be present in silo systems,
especially in areas like supplier management. AI is indeed a great method for enhancing
efficiency, understanding data and driving actions; it can’t be a replication
for the right relationship management driven by the SCM team
Concluding Notes
Today, most of the companies operating across the world are deploying traditional practices in supply chain management for expanding their customer and supplier base. When Ai technologies are applied in the SCM, it offers benefits like- enhancing tracking of products, smarter inventory management, computer-aided quality inspection. AI in SCM also helps in minimizing human errors and smoothening the key business processes.
