AI in the supply chain promises a more streamlined and efficient way of operating.

Recently, people have become aware of the fragility of the global supply chains. These far spreading networks, crucial for manufacturers everywhere, are often plagued by logistic challenges, labor stoppages, growing complexity, which worsen their current problems.

To untangle these closely knitted networks, supply chain planners are leveraging a cutting-edge technology that proffers exceptional, still largely untapped potential. This is where AI in supply chain management is put to work to make the entire process more efficient and resilient, with we heading into an increasingly globalized future.

AI in Supply Chain – What, Why and Where?

Believe it or not, artificial intelligence’s future is strong among technology enthusiasts.

Businesses are leveraging AI to manage supply chain activities – like balancing inventory, monitoring product quality, identifying fuel-efficient delivery routes – with more efficiency compared to conventional software.

Thanks to Machine Learning (a subset of artificial intelligence), AI systems can outperform conventional software in activities like understanding information from videos, interpreting verbal and written text, predicting future market behaviors, making decisions in complicated situations and surfacing insights from huge data sets.

For example, AI can analyze factors like traffic and weather conditions to suggest alternative shipping routes, minimizing the risk of unplanned delays and improved delivery times. Surprisingly, it can track workspaces to identify poor quality processes and any health or safety violations.

Why is AI in Supply Chain the Need of the Hour?

Companies are establishing AI in supply chain management software to help optimize distribution routes, manifold warehouse productivity, streamline factory workflows and much more.

Primarily, manufacturers depend on hundreds, if not thousands, of elements shipped from partners across the globe to arrive in their assembly on a coordinated schedule. Here, AI assists by identifying patterns and relationships within huge data sets that helps in optimizing logistics networks from cargo freighters to distribution centers.

Some manufacturers are harnessing AI in forecasting, using it to predict production and optimize warehouse capacity considering the customer demand. A handful of them are integrating AI to flag potential bottlenecks and tools malfunctions before they cause any production problem. Besides, AI can be utilized to get operational insights from behemoth data inflow from emerging IoT (Internet of Things) and sensors established across their storages and transportation infrastructure.

Where Can Artificial Intelligence Enhance the Supply Chain?

Today’s supply chains have become so intricate, entangled and wide-ranging that manufacturers often face demur in maintaining end-to-end flow of materials and goods reaching their premises. Fortunately, AI’s unique capability to quickly analyze data sets can highlight the inner workings of the most complex logistics networks.

AI-driven supply chain management tools are better than conventional systems at monitoring voluminous quantities of supplies in real time as they funnel through intermediary manufacturing and distribution partners in the process of becoming the final product.

Organizations can’t afford to work with suppliers, especially those rooted overseas – to manage concerns like infringe on labor, good governance or environmental rules. Thus, AI-enabled supply chains provide improved visibility and traceability to help manufacturers identify suppliers who are potentially compromising ethical sourcing practices or quality.

Here’s Why Businesses Like You Can’t Afford to Overlook AI in Supply Chain Management  

9 Benefits of AI in Supply Chain for Businesses

Manufacturers have been spearheading AI innovations, experimenting and integrating different forms of the technology across different aspects of production facilities, distribution centres and storages and logistic vehicles in modern supply chains.

Let’s look at the top 9 benefits AI ushers in the supply chain management

1. Enhanced Warehouse Efficiency

Undoubtedly, AI makes warehouses more efficient by assisting in organizing their racking and layouts designing. By evaluating the quantities of materials transported through warehouses, Machine Learning models can recommend floor layouts that accelerate access and travel time of inventory – from receiving racks to packing and shipping stations.

Moreover, they can plan optimal routes for workers and robots alike to shuttle inventory faster, further boosting productivity rates. By analyzing demand signals from marketing, point-of-sale systems and production lines, AI-driven predicting systems help manufacturers balance inventory against shipment costs, further optimizing warehouse capacity.

2. Huge Savings on Operating Costs

With AI’s potential to learn complicated behavior and work under unpredictable conditions, repetitive tasks, like

With AI’s ability to learn complex behaviors and work under unpredictable conditions, repetitive tasks, such as counting, tracking, and documenting inventory, can be completed with greater accuracy and less labor; bottlenecks are identified and mitigated. By identifying inefficiencies and learning from repetitive tasks, AI can reduce the cost of operating a complex supply chain.

AI can also save manufacturers and distribution managers money by reducing the downtime of vital equipment. Intelligent systems, especially those processing data from IoT devices in smart factories, can identify malfunctions and breakdowns in their early stages or predict them before they happen, limiting disruptions and the associated financial losses.

3. Less Errors and More Sustainable

AI can easily spot anomalous behavior from machines and humans quicker than we can.

This is why everyone from the hierarchy is training algorithms to expose errors in their workflows, product flaw and employee slip-ups. Cameras equipped with logistic hubs, delivery vehicles, and assembly lines feed into computer vision systems that use AI to analyze work and save on recalls, returns and rework.

The AI-enabled system can identify mistakes before products are misassembled or sent to wrong destinations, saving efforts, materials and time. Smart systems can also carry root cause analysis, assessing large volumes of data to detect correlations explaining failures and equip teams to make better decisions sooner.

💡 AI can be embedded in ERP systems to manage financial transactions as good flows through supply chain, assisting businesses avoid any costly slip ups and payment errors.

4. Precise Inventory Management

Manufacturers are utilizing AI’s potential to manage their inventory levels with greater accuracy and efficiency. For instance, AI-driven forecasting systems can utilize inventory information shared from downstream customers to gauge the respective demand. So, if the demand is growing, then it’ll automatically alter the manufacturer’s demand forecast accordingly.

Supply chain managers and manufacturers alike are establishing computer vision systems – integrating cameras on supply chain infrastructure, vehicles, racks and even drones – to tabulate goods in real time and track warehouse storage capacity. Artificial Intelligence tracks these workflows in inventory ledgers and automates the procedures of creating, updating and extracting information from inventory documentations.

5. Optimized Operations With Simulations

Leverage AI-powered simulations to get comprehensive insights into the operations of complex, global logistics networks and simultaneously identify ways to improve them.

Surprisingly, the increased use of AI is seen in conjunction with digital twins – a 3D graphical representation of physical objects and processes, like factory production lines or gathered goods. The operational aspect can simulate numerous methods and approaches on digital twins – how much output would increase if they increase capacity at point A compared to point B? And gauge results without interrupting real-world operations.

When AI is incorporated into the models and controls the workflows, these simulations turn more precise than the one run with traditional methods. This AI application helps engineers as well as production heads to evaluate the impacts of redesigning products, installing new machines or replacing the parts in the factory. Besides, AI and ML also helps in creating 2D visual models of external processes to determine the potential impact of changing suppliers, redirecting shipping or distribution routes or even relocating warehouses, etc.

6. Improved Material and Worker Safety

AI in the supply chain can monitor everything from storage facilities to flag conditions that jeopardize the safety of workers and the public. This might mean using computer vision to enforce the use of PPE (Personal Protective Equipment) or check if workers adhere to company protocols and OSHA (Occupational Safety and Health Administration) standards.

Surprisingly, AI-powered wearable safety devices increase protection. Imagine a sensor-enabled vest that is connected to AI-systems, analyzing warehouse workers movements and notifying them of the injury based on their posture, movements or location in the warehouse.

Nowadays, the most pressing question is “how can AI enhance sustainability in supply chains”?

In distribution facilities, AI helps ensure that hazardous materials are properly handled and disposed of, securing those who dwell and work nearby. For instance, AI-enabled bots plot the most efficient route through a warehouse, then transport hazardous materials while avoiding objects in their paths and relaying results to a warehouse management system. In case of any failure or accident, AI can perform analysis to identify their exact causes and prevent repeats.

7. Timely Deliveries

Manufacturers that collect products through complex supply chains are highly dependent on timely and well-oriented deliveries. Thus, delayed deliveries of the single component can hinder the entire production schedule.

Simply put, AI is taking big on minimizing these delivery holdups.

Logistic companies are leveraging machine learning to train models that optimize and manage the delivery routes by which every component will follow along the supply chain. Moreover, these shipments can prioritize shipments based on order volumes, contractual deadlines, customer importance and much more. Also, they provide all nodes in the distribution network with more-accurate ETA, identifying shipments that, if delayed, can create fuss.

8. Accurate Demand Prediction

AI is etched as the golden standard for forecasting demand based on both internal data signals, like sales pipelines and marketing leads, external signals like economic outlook, seasonal sales trends.

Supply chain planners can leverage AI integration in demand planning software to circumscribe not merely demand but also the potential impact of scenarios like severe weather conditions or economic downturns, production capabilities and ability to make deliveries.

9. Enhanced Supply Chain Sustainability

AI can make supply chains more sustainable and minimize their harmful environmental impacts. For instance, ML-trained models prove beneficial in assisting organizations reduce energy consumption by optimizing truckloads and delivery routes to ensure less fuel burning.

Artificial Intelligence can also be used to analyze the lifecycle of finished products and simultaneously deliver insights that contribute to a circular economy, where materials can be reused and recycled. Furthermore, supply chain planning and sourcing systems with built-in AI manifolds transparency across suppliers, allowing them to adhere to both social as well as environmental sustainability standards.

Finally… Integrate AI in Supply Chain with Apptunix

If you are looking to leverage AI in your logistics business software, look no further than Apptunix. Here’s why:

Apptunix is a leading AI app development company, seamlessly integrate AI into logistics software. Our dedicated team starts by analyzing your current systems and identifies areas for improvement. Next, we develop AI-powered tools like predictive analytics to forecast demand accurately; helping in maintaining inventory.

We optimize processes ensuring efficient and timely transportation using AI tools. Notably, our machine learning algorithms continuously learn from data, enhancing overall performance.

Additionally, we offer an AI-powered tracking system to manage shipments in real-time, boosting security and reliability. Leverage our experience and expertise in this technology to manifold your ROI seamlessly.