Benefits of Artificial Intelligence in Supply Chain Management
Published: 2022-06-14 09:11:45

[International Data Corporation](https://www.idc.com/in/?utm_source=press-release&utm_medium=website&utm_campaign=india) (IDC) expects that by 2024, 40% of large corporations will use AI and machine learning across all business-critical horizontal functions, such as marketing, legal, HR, procurement, and supply chain logistics. According to the report, companies would also stop relying solely on short-term demand estimates.


![Impact of AI in Retailors](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/ekkp4pfh0gjb7t5a46z1.png)


According to Gartner, supply chain firms expect machine automation to double in their supply chain activities in five years. At the same time, a recent study from [Forbes](https://www.forbes.com/sites/louiscolumbus/2019/06/02/seven-things-you-need-to-know-about-iiot-in-manufacturing_updated/?sh=8a718445f561) predicts that global spending on IIoT Platforms will expand from $1.67 billion in 2018 to $12.44 billion in 2024, representing a 40% compound annual growth rate(CAGR) in seven years.

In today's supply chain optimisation, artificial intelligence plays a critical role. Would you like to learn more about the fascinating impact AI can have on the supply chain industry? Then, make sure to be hooked to the article until the end.
##Artificial Intelligence: Overview

### Definition of AI

Before we get into the meat of the matter, we'll go through the basics of artificial intelligence. AI, by definition, is a system that is capable of accurately understanding external input, learning from it, and applying that learning to achieve a goal and adjusting its behaviour accordingly.
### Astonishing Statistics of AI

- According to Gartner, AI software will be worth $62 billion in 2022, up 21.3 % from 2021.
- AI is expected to grow at a 33.2 % annual rate between 2020 and 2027, according to Semrush.
- By 2020, 80 % of marketers will have implemented chatbots as part of their customer service strategy.
- By 2030, global GDP will have increased by $15.7 trillion.
- By 2023, AI-powered voice assistants will be a total of 8 billion.
- Over the previous two decades, the number of AI startups has increased 14-fold.

## Characteristics of AI

Since World War II, the field of artificial intelligence has gained traction, and John McCarthy popularised the phrase in 1956, and from then, there's been no turning back. As a result, artificial intelligence is becoming a must-know topic in nearly every industry, including the automotive industry, sports, healthcare, advertising, and science and engineering.

These are the characteristics that define AI:

- Eliminating tedious tasks
- Preventing natural disasters 
- Ingestion of data
- Chatbots and Facial Recognition
- Futuristic thinking
- Imitating human cognition

## AI Applications Within Supply Chain Activities
Incorporating artificial intelligence into the supply chain is primarily intended to create a completely automated and fully-customized decision-making process. Businesses can predict demand surges and adjust material flow routes and volumes with the help of AI-enabled supply chain management.

Artificial intelligence can be used by organizations to compile vast amounts of data that could impact delivery timetables. These analyses can help sales teams predict delivery schedules. Customers are informed of current inventory levels in real-time. Consequently, businesses can provide better service to present and potential customers.

Let's look at four critical areas where AI can be put to good use.

### 1. Supply Chain Planning with Machine Learning
[Supply chain management](https://www.parangat.com/blockchain-supply-chain) is useless without supply chain planning. Businesses can forecast inventories, demand, and supplies using machine learning (ML) in supply chain planning. The flexibility and efficiency of supply chain decision-making can be revolutionised by machine learning.

With machine-to-machine analytics and clever algorithms of massive data sets, supply chain specialists can deliver the best conceivable scenarios using ML technology. Machine learning allows merchants to improve goods delivery in the supply chain while regulating supply and demand.

### 2. Operational Procurement Chatbots
Businesses can benefit from chatbots in various ways, including lower transaction costs and shorter sales cycles. In addition, through the automated and augmenting process, chatbots can help to streamline procurement-related activities.

How can chatbots help in the supply chain?

Have a conversation with suppliers about the most typical issues.

Conduct internal research and provide answers to procurement-related queries.

Notify suppliers of activities relating to governance and compliance materials.

Invoice and payment request documentation

### 3. NLP in Supply Chain
NLP is a blend of AI and machine learning that allows humans to engage with devices and data through natural dialogues based on text and voice. It can be used in the supply chain in a variety of ways. For example, using natural language processing (NLP) in supply chain management helps reduce administrative costs.

NLP has a lot of potential for quickly deciphering enormous volumes of foreign language data. Due to language barriers, NLP offers the ability to develop data sets about suppliers and decode latent knowledge. NLP technologies can accelerate audit and compliance procedures that were previously impossible due to language constraints between customers and suppliers from a sustainable development and governance standpoint.


### 4. Warehouse Management Using Machine Learning
Proper warehouse and inventory-based management are essential to supply chain planning. Supply shortages (overstock or understock) can become a significant issue for any consumer-based business. Retailers can use a forecasting engine with machine learning to see which algorithms and data streams have the best predictive ability for various prediction hierarchies.

## Benefits of AI in Supply Chain Management
Because of the interlinked and globalised context in which we live, current supply chains are intricate and highly quick at any commercial level. With this level of speed, the human error must be minimised, and the effectiveness of all of these operations must be enhanced, which is why AI has gained traction in this industry in recent years. 

Information retrieval, data processing, supply and sales forecasting, automated vehicles, and logistics planning are just a few artificial intelligence applications in the supply chain. Some of the advantages AI provides in logistics and supply chain management are as follows:
### 1. Proper Inventory Management
Proper inventory management ensures that commodities enter and leave a warehouse in a timely manner. Variables related to inventory, such as pick-up, packing, and order processing, can be extremely time-consuming and error-prone. A proper inventory management system can, however, prevent overstocking, inadequate supply, and unexpected stock-outs.

Using AI-driven inventory management technologies can be highly effective due to their ability to handle large amounts of data. By analyzing large datasets, these algorithms can offer timely supply and demand forecasting advice. Due to their clever machine learning algorithms, these AI systems can also anticipate and identify new consumer patterns as well as estimate seasonal demand.

### 2. Efficiency in Warehouse Management and Control
Supply chains cannot function without an effective warehouse. Retrieving items from warehouses and delivering goods to customers are both made easier by automation. Artificial intelligence technologies can address a wide range of warehouse issues faster and more precisely than humans, as well as ease complex procedures and accelerate productivity. 

A warehouse with AI-driven automated efforts can save significant time and money by reducing the need for warehouse personnel.
### 3. Improved Safety
Automated technologies based on artificial intelligence can improve warehouse management, employee safety, and product planning. Furthermore, AI can assess data on worker safety and notify manufacturers of potential threats. 

Stocking factors and operations can be monitored, as well as feedback mechanisms and preventative maintenance. Keeping warehouses safe and compliant with safety regulations can be done quickly and aggressively by producers.
### 4. Minimized Operational Costs
AI systems offer tremendous advantages to the supply chain in this regard. Automated intelligent processes, from customer service to warehousing, can operate without errors for long periods of time, reducing workplace accidents and mistakes. The accuracy and speed of warehouse robots have improved productivity.

### 5. On-Time Delivery
AI tools make processes faster, simpler, and smarter by reducing reliance on manual labour. Consequently, consumers receive their goods on time, as promised. By automating warehouse procedures, operation constraints along the supply chain are eliminated with minimal effort required to meet delivery targets.

## Impacts of AI on Logistics and Supply Chain
The captivating factor of AI is its virtually infinite potential. When combined with other technologies such as [machine learning](https://www.parangat.com/machine-learning), the IoT, and predictive modelling, algorithms grow more powerful. 


![Impacts of AI on Logistics and Supply Chain](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/k4g2tz1cgids5puxfn9j.png)

Companies can better understand their worldwide logistics networks with more data. Our definition of logistics and supply chain management is evolving, which is why transparency is so crucial.

AI has the potential to have a significant impact in five major areas:
### 1. Skyrocketing Predictive Capabilities
AI's ability to predict demand and plan networks enhances the efficiency of organisations greatly. If companies have accurate demand forecasts and capacity planning tools, they can be more proactive. By predicting demand and directing the vehicles where they are needed, they can reduce the number of vehicles required for transportation, resulting in lower operating costs.

By using technology to utilize data, it is possible to forecast occurrences better, avert dangers, and offer solutions. AI can solve these equations faster and more precisely than ever before, enabling businesses to adjust how their resources are allocated for optimal benefit.

### 2. Robotics
When discussing artificial intelligence, the field of robotics must be mentioned. Even though they may seem futuristic, they are already present in the supply chain. 

According to [Tractica](https://www.fierceelectronics.com/components/warehousing-and-logistics-robot-shipments-will-reach-620-000-units-annually-by-2021) Research, global warehouse and logistics robot sales will reach $22.4 billion by 2021. Inside warehouses, robots track, monitor, and move merchandise, while at ground distribution hubs, they transport and sort oversized packages.
### 3. Clean Data
AI in logistics organizations has become increasingly dependent on clean data generation, as many of them lack suitable figures. In addition, efficiency benefits are challenging to quantify since some businesses collect data from various sources and multiple employees. 

However, because such figures are difficult to change at the start, algorithms have been used to analyse historical data, detect problems, and enhance the quality of the data to the point where significant corporate transparency is achieved.

Electricity is also increasingly being used in these self-driving cars. Historically, charging ranges have been a problem. Even so, electric cars are rapidly expanding their range capabilities, with Tesla announcing last year that its Semi Truck can travel 800 kilometres on a full battery charge and an additional 600 kilometres with only 30 minutes of charging.

### 4. Computer Vision
An extra set of eyes is always useful when transporting cargo around the world, and this is especially true when those eyes are equipped with cutting-edge technology. We are observing the supply chain in new ways thanks to artificial intelligence based on computer vision. DHL says visual inspections enabled by artificial intelligence can spot "damage, categorize the damage type, and decide the relevant corrective action" faster than ever before.

AI can find the unknown parameter based on past shipments, even if organisations lack sufficient shipment data. To build a training dataset that can be used as a foundation for data purification and enrichment, these algorithms only require 5 to 10% of valid data. Based on the data, an accurate look at the fullness or emptiness of the vehicle can be determined.

### 5. Autonomous Vehicles
Finally, there is the self-driving car. In the logistics industry, high-tech driving support is improving safety and efficiency despite the fact that fully autonomous trucks are still a ways off. With highway autopilot, lane-assist, and assisted braking capabilities, the trucking industry is expected to be fully autonomous in the near future.

Several trucks can take advantage of improved driving technology to save fuel. They follow the other trucks in their fleet closely as they are precisely controlled by computers interacting with one another in a process known as platooning. In terms of fuel economy, these driving formations saved the leading truck 4.5 % and the following truck 10%.

## Reinventing Supply Chain with AI
Businesses can use AI in supply chain management to analyse and track data, spot abnormalities, and make predictions to optimise supply chain operations. In addition, artificial intelligence has the potential to improve supply chain agility and precision.