AI in Supply Chain Management: Benefits, Key Technologies, Top Applications

As companies expand their reach globally and customer expectations about the buying experience continue to rise, managing shipments across complex networks has become more complicated for suppliers and fulfilment partners than ever.

Even a single disruption, such as a labour shortage or a factory shutdown, can create a ripple effect down the supply chain, ultimately leading to customer dissatisfaction and revenue loss.

By utilising Artificial Intelligence (AI) in supply chain management, companies can optimise activities like planning, production, and route management based on real-time data insights. In this blog post, we offer a brief overview of what that looks like.

What Is AI in Supply Chain Management?

AI refers to the simulation of human intelligence by applications to perform complex activities like learning, problem-solving, and decision-making. There are several subsets of AI, including Machine Learning (ML), Internet of Things (IoT), Natural Language Processing (NLP), Robotic Process Automation (RPA), and so on.

Essentially, AI can study vast volumes of data to uncover patterns and anomalies that manual effort would miss, enabling companies to make informed decisions and predictions.

Over the last several years, AI has been applied to several aspects of supply chain management, such as tracking inventory, ‌streamlining factory workflows, optimising shipping routes, maintaining the integrity of transaction records, and so on.

Most supply chains are highly complex, with multiple moving parts, from sourcing product components to maintaining complicated machinery to scheduling shipments.

AI particularly enables manufacturers to gain control over these moving parts and make the most time-saving and cost-effective decisions at every step.

Benefits of AI in Supply Chain Management

AI offers visibility, transparency, time savings, and cost savings on an unprecedented scale for modern supply chains. The benefits of AI in supply chain management include:

1. Cost reduction

AI can study thousands of data points to offer unique insights on where and how companies can save money, such as by swapping freight providers or using a more cost-efficient packing material. Plus, learning tasks and executing them quickly helps manufacturers get things done much faster than hiring a human team. 

2. Increased efficiency

AI helps manufacturers fulfil orders faster and more accurately than ever before. From demand forecasting to automatic records and updates, optimised route suggestions, and enhanced quality checks, AI supply chain management offers a far more streamlined experience than traditional supply chain management.

3. Enhanced decision-making

AI-driven systems can study historical and real-time data to identify the root cause of a problem and deliver a solution almost instantly. This enables faster decision-making even in urgent situations, a significant advantage in a volatile economy. 

4. Real-time data and insights

AI algorithms can be leveraged to study behaviours and rectify any problems early on, such as a failing machine or a product defect. They also offer real-time insights on customer demand patterns, enabling manufacturers to recalibrate their inventory and fulfilment plans as necessary.

5. Sustainability and environmental impact

AI can help identify inefficiencies that lead to waste in production and logistics, enabling more sustainable supply chain practices. Optimising logistics, transport routes, and production schedules help companies reduce their carbon footprint and contribute to environmental sustainability.

Key AI Technologies Transforming the Supply Chain

Companies in the manufacturing space are employing AI in diverse ways throughout the length of the supply chain. Some of the popular technologies involved include:

• Applying machine learning in supply chain greatly helps decision-making, as it can study data sets and proactively learn from them. For instance, ML models can study the quantity and nature of goods moving in and out of a warehouse to suggest optimum layout patterns for storing goods.
• RPA is invaluable for automating repetitive tasks, such as updating the movement of physical goods, extracting and classifying data from text files, placing inventory orders, processing customer orders, scheduling deliveries, and so on. 
• NLP can mimic human-like communication, including regional dialects and turns of phrase. This is a valuable technology for customer interactions at scale, as companies can automate the process while retaining the feel of a human conversation. 
• AI-powered computer vision can rapidly scan products and machinery to flag errors, enabling speedy quality checks and highlighting any repairs/replacements needed in factory equipment before major problems arise. 
• IoT is rapidly emerging as a critical technology for real-time tracking. By enabling constant communication among an interlinked set of devices, the technology can raise alerts about stocks running low and automatically change delivery routes if a delay emerges on the current route.
• It can also help workers quickly locate SKUs in a warehouse, adjust environmental conditions in storage containers to preserve the freshness of goods, and so on. 

Real-world Applications of AI in Supply Chain

Here are some of the ways AI is helping companies build more resilient supply chains:

1. Quality control

AI can scan products, detect defects or anomalies, and update details to a central dashboard for fast, efficient quality checks. It can also offer smart insights on packaging and storage to preserve item quality as transported down the supply chain.

Many automotive companies, like BMW and Audi, use AI-powered vision systems to inspect parts for defects. These AI systems flag inconsistencies and defects in real-time, minimising rework and ensuring higher-quality production.

2. Route optimisation

AI in logistics can intelligently study transportation networks, from warehouses all the way to last-mile distribution centres, and determine the fastest and most efficient route for each shipment.

DHL indeed uses AI to optimise routes, leveraging real-time traffic, weather data, and other factors to determine the most efficient delivery paths.

3. Demand forecasting

AI can study historical consumer data as well as market trends (such as seasonal shifts, political factors, current events, etc.) to help manufacturers forecast demand and thus plan their production and warehouse capacity in advance.

Walmart, Target, and Macy’s use AI for demand forecasting, particularly during peak shopping periods like Black Friday. By analysing large datasets of historical purchases and external trends, they can predict and meet consumer demand with high accuracy.

4. Warehouse automation

More and more factories are investing in AI for warehouse automation. From maintaining minute logs of activity to powering autonomous machinery, conducting granular quality checks, and auto-flagging any maintenance needs, AI helps manufacturers run a tight ship with their production.  

Amazon optimises warehouse operations by using robots (Kiva Systems) in its fulfilment centres. These robots, guided by AI, make the picking and packing process more efficient.

5. Inventory management

With granular insights into customer demand, manufacturers can produce only what is needed, thus avoiding the risk of overstocking or stockouts.

AI also helps streamline inventory management by automating the documentation of each SKU, providing insights into storage ideas for maintaining product quality and updating the system every time goods flow in or flow out.

IKEA uses an AI-powered inventory system, which predicts stock needs based on local trends, warehouse space, and even environmental factors like weather patterns that could affect transportation.

6. Supplier relationship management

AI makes it easy to maintain communication with your suppliers and transport partners.

All updates and documents can be shared on a centralised platform, with auto-notifications whenever something changes. This helps everyone stay on the same page about each shipment and improves mutual trust and collaboration.

Future Trends of AI in Supply Chain Management

The potential for AI in supply chain management remains largely untapped. Around the world, manufacturers and researchers are finding newer and newer ways to put this technology to good use:

1. Simulations

Many supply chain managers are leveraging the power of digital twins along with AI to create powerful simulations that identify process inefficiencies, potential disruptions, and product/packaging defects with unprecedented clarity.

Through simulations, companies get visual insights into their supply chain that are easy to understand and useful for demonstrating to stakeholders.

2. AI and Blockchain

Blockchain is an emerging technology that can offer unprecedented degrees of transparency for every stakeholder in the supply chain. 

All transactions are recorded on a securely shared ledger, enabling complete traceability while reducing the administrative burden of maintaining records. This helps forge trust among global value partners by creating a single, encrypted source of truth.

3. Sustainability and AI

The supply chain industry has long been criticised for its poor adherence to sustainability practices, and AI can help change that. For instance, it can map the most fuel-efficient delivery routes and suggest the optimum amount of packaging material for each item.

It can also help manufacturers make the right choices by flagging vendors or locations that might be known for unethical practices. 

4. AI and autonomous vehicles

Experiments on autonomous vehicles have already begun, and AI has the potential to revolutionize the fulfillment process of orders with drones and driverless vehicles.

They can cover longer distances faster than human drivers and make smart decisions about which path to take based on real-time inputs about road conditions or fuel-efficient options.

Final Words

Global supply chain networks are becoming increasingly complex, and the only way for companies and manufacturers to keep pace with that growth is by gaining visibility and control over the entire process.

Therefore, now more than ever, it’s vital for them to invest in supply chain optimization with AI-powered systems.

To enhance your supply chain capabilities, consider investing in custom AI solutions from Intuz, designed for your specific products and fulfillment processes.

That way, you benefit from granular insights on how to save money, fine-tune your supply chain, and meet your ethical and corporate responsibilities. Good luck!