Artificial Intelligence (AI) in Supply Chain and Logistics

 Supply chain and logistics are critical in every industry and given the amount of data generated by logistics, supply chain and transportation, are steadily gaining attention from various AI startups and vendors. Artificial intelligence provides various techniques to analyze huge amounts of data collected from supply chain and logistics and derive actionable insights that can enable processes and complex functions. 

Regardless of techniques and tools, these are two core functionalities that must be achieved by any AI technology

Augmentation: Augmentation, basically, reduces errors caused by human bias. It helps humans in their daily tasks, without having full control over the outcome. Virtual assistants are the best examples of growth.

Automation: Automation refers to the use of machines to perform tasks without the need for human intervention. Robots performing critical steps in a manufacturing plant is the best example of automation.

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AI in Supply Chains and logistics

1. Demand forecasting

Machine learning is a mathematical approach used to identify patterns and influential factors in supply chain data with algorithms, and the outcome of each decision is constrained by minimum and maximum range constraints. This data-rich modeling empowers warehouse managers to make more educated decisions about inventory stocking.

This type of big data predictive analytics will transform the way warehouse managers manage inventory by providing deep insight that is impossible to unravel with manual, human-driven processes and endless, self-improving forecasting loops.

2.Automated decision making

Artificial intelligence can reinvent business models by revamping the way you look at future trends. AI has the ability to analyze today's activity patterns to predict the possible outcomes of tomorrow's scenarios. It is used to automate lower-level decision making and balance supply with forecasted demand. Managers immerse their skills in high-level decision making and strategy.

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3. AI in procurement

AI was initially limited to automating the processes of collecting, classifying and analyzing organizational costs. But today, the technology is finding widespread use as companies leverage cognitive procurement advisors (CPA) and virtual personal assistants (VPA) that implement AI functions such as natural language processing and natural language generation.

VPAs have the potential to improve end users' experience. They can also guide people to relevant purchasing tools. CPAs, on the other hand, can provide integrated summaries and advice about multiple processes throughout the entire procurement cycle. It also includes supplier assessment, performance management, risk management and compliance.

Reduce risks

Supply chain management processes are only effective if inventory is well managed. If a supplier fails to meet demand, time and money invested in it will be wasted and customers will be dissatisfied. AI mitigates these risks with the help of predictive capabilities. It can predict the upcoming demand of products, bring transparency to the entire process and influence decision making.

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Increase productivity

Analyzes the performance of AI in supply chain management and anticipates new issues and opportunities in the same area. It utilizes the capabilities of various techniques such as supervised learning, unsupervised learning and reinforcement learning to identify problems in the supply chain. These insights help eliminate time-consuming tasks and increase overall productivity.

Improve customer service

AI plays a key role in personalizing customer experiences. A personalized customer experience improves the relationship between logistics providers and their customers. AI-based systems enable voice-based shipment tracking, which allows customers to directly contact the customer support team in case of any issues, thereby improving customer service.

Read More: How Much Does It Cost to Develop a Voice Chat App like Clubhouse

Chatbots

AI-powered chatbots in the supply chain like Procuebots are also gaining immense popularity. You can use these for a range of everyday tasks:

● Interacting with suppliers during informal conversations.

● Automate placement of purchase requisitions.

● Conducting actions related to governance and compliance materials.

● Investigating and answering questions about the procurement process or suppliers. Receive, review and file documents related to invoices, payments, order requests and more.

● Effective handling of procurement emergencies.

The Future of AI in logistics and supply chain

We expect AI systems based on deep learning algorithms to be widely used in the near future by companies willing to optimize their business operations. These ML models help companies process big data and make decisions with greater accuracy.

The use of Artificial intelligence applications is expected to increase significantly, mainly due to an increasingly competitive environment and an ever-changing global economy that forces businesses to explore new ways to achieve better results. 

These technologies provide an opportunity for faster decision making to improve overall efficiency. The most important benefit of deep learning algorithms is the level of automation it enables, which has a significant impact on reducing costs in all areas of logistics and supply chains. We believe that there are endless possibilities of applying this technology across different domains that will bring benefits to society.