How can AI transform the supply chain?

  • By Henk Kooijman
  • 09-05-2024
  • Artificial Intelligence
ai in the supply chain

Integrating artificial intelligence (AI) into supply chain management has emerged as a game changer in today’s business environment. It makes things work smoother and helps make better decisions. AI in the supply chain gives plenty of good stuff like better sales, agility, and competition as businesses go worldwide and start using smart, data-guided solutions.

Appvin Technologies is a leading cross-platform application development company that can empower your business with a range of services, including supply chain analytics, data visualization, data warehousing, and business intelligence solutions. As businesses tackle the tricky global market and the changing wants of customers, AI is showing up as a trigger for never-seen-before efficiency, adaptability, and creativity in the supply chain.

Artificial intelligence, or AI, is a super-high technology in today's era. It reshapes how we work, make choices, and streamline tasks. According to data from Statista, AI in supply chains is the top solution. It helps manage stock, smartens up manufacturing, revolutionizes delivery systems, and controls delivery times. Use AI to make supply chains and logistics better and more productive. Additionally, by adding AI to supply chain management, things have become more sustainable.

However, in this article, we will explore the impact of artificial intelligence (AI) on supply chain management.

Additionally, we will highlight how our company, AppVin, is contributing to this journey by developing mobile app solutions designed to enable companies to harness the full power of AI in supply chain management. 

Benefits of using AI in supply chain management

Supply chain management is about maintaining the flow of goods and services and optimizing business processes.
From specifying raw materials to managing trusted vendors, automating warehouse operations, and optimizing shipping paths and delivery schedules, every stage of the supply chain needs to function efficiently to improve your bottom line and give you an edge over your competitors.

Moreover, fresh research reveals that 37% of firms, supply chain businesses included, utilize artificial intelligence (AI) in their operations. By 2030, AI could contribute a staggering $15.3 trillion (about $47,000 per person in the US) to the global economy. Here are a few ways AI boosts supply chain management:

Demand Planning and Accurate demand forecasting

Demand planning and accurate demand forecasting are key to good supply chain and inventory control. AI algorithms use lots of data, like past sales data, market patterns, customer habits, weather and economic conditions, and other external things, to make really accurate demand predictions.

Furthermore, this helps companies plan their product making, inventory amounts, and quality distribution channels. AI algorithms study past sales data, market patterns, weather, and other useful factors to get accurate demand predictions. By using machine learning models, companies can better guess changes in demand, make inventory amounts just right, and avoid times without stock or with too much stock.

Additionally, by using machine learning algorithms and models, companies can better predict changes in demand, optimize inventory levels, and minimize situations of stockout or overstock.

Transportation and Logistics Route Optimization

AI systems optimize travel paths, store de­signs, and shipping calendars. They use factors like­ street congestion, gas prices, and shipping priorities.

However, implementing these operations cuts down on travel expenses, makes deliveries faster, and boosts total efficiency. Travel and logistics are crucial parts of the package. AI in supply chain will help plan out and streamline routes for better savings. They could work out the best routes, decrease gas use, cut down emissions, and guarante­e deliveries arrive on time.

Asset management and maintenance: predictive maintenance

AI assists in predicting maintenance through sensors, IoT gadgets, and detailed analysis. This predicts possible malfunctions faster and stops them in their tracks. Companies want to cut down on downtime, save on fixing devices, and make their tools last longer.
Consequently, the way a supply chain works hinges on tools and many other devices, from creation to transportation. Predictive maintenance empowered by AI in supply chain keeps an eye on these assets 24/7. It le­arns from data gathered by sensors and IoT gadgets to spot possible failures. This method lessens the impact on productivity, makes assets last longer, and cuts the chances of supply chain hiccups.

Supply chain performance depends on equipment and a wider range of devices, from manufacturing to transportation. AI-powered predictive maintenance can monitor these assets in real-time, analyzing data from sensors and IoT devices to identify potential failures or breakdowns before they occur This approach can reduce operational efficiency by extending asset life and reducing supply chain disruptions.

Inventory Management and Optimization Intelligent inventory management

AI is set to transform how we manage inventory, offering live updates on stock throughout the supply chain. By using machine learning, it can hone inventory management based on demand trends, customer habits, and supply chain movement, lessening the danger of stock running low or piling up.

Additionally, AI can take care of restocking and resupplying, smoothing out the whole inventory oversight process. Real-time insights into supply chain operations are made possible by AI's analytical capabilities, letting businesses keep an eye on supply chain advancement, assess supply chain effectiveness, and pinpoint potential roadblocks or issues. This increased discovery drive fosters proactivity and teamwork within the supply chain ecosystem.

Customer service and engagement: AI-driven chatbots and virtual assistants

AI-supported chatbots and helpers can boost customer help in the supply chain by giving quick info on order status, delivery dates, and any issues or suggestions. These AI-bot programs can answer common questions, leaving human workers to handle tough jobs and boost customer appreciation.

As AI knowledge grows, so do its uses in the supply chain. By accepting AI, businesses can get a step ahead, speed up actions, cut down on costs, and make a better customer journey. However, the­y must closely check AI solutions when dealing with moral questions, data secrecy, and emotion recognition.

Warehouse Automation and Optimization Warehouse

Warehouse optimization can change in a big way with AI in supply chain. It becomes super-efficient and cost-effective. Self-driving vehicles and robots can take on jobs like sorting, putting things in boxes and picking things up. AI software can arrange the warehouse and items to make things quicker and help with filling orders.

Furthermore, with AI handling logistics in warehouse operations, workers get a comprehensive toolkit for all their tasks. These range from dealing with arrivals, organizing goods, and packing to dispatching. Plus, having a barcode scanner function simplifies inventory management for workers. It helps reduce errors and boost efficiency.

Risk Management and Supplier Analysis

Businesses can get hit hard by supply chain issues. But AI in the supply chain can step in and lower these risks. It looks at how suppliers are doing. Delivery times, quality checks, and money matters, as well as things like political risk and natural disasters, are all put under the AI microscope. From there, it can point out dangers and suggest ways to help or other suppliers to use.

Consequently, AI, with special tools like predictive analytics and algorithms, analyzes old and new data and predicts where problems might occur. Supply chain stakeholders use AI tools to plan solid ways to handle these risks. AI sheds light on the supply chain 24/7, giving important information that helps make smart choices. For example, Microsoft uses AI to minimize its supply chain risks. Their AI system is online all the time, guiding them about their whole supply chain and helping them effectively handle risks. This way, Microsoft uses AI technology to expect, find, and deal with risks on time.

Steps to Optimizing the Modern Supply Chain with AI and Data-Driven Strategies

Here are the following steps to optimizing the modern supply chain with AI and data-driven strategies:.
These are the following:

Defining Goals

The first step to optimizing the modern supply chain with AI and data-driven strategies is to first decide what you want to get from adding AI and data analysis to your supply chain tasks. Work with stakeholders and experts for tasks like forecasting demand, managing stock, planning routes, or controlling risks. Creating plain templates will steer the creation and use of AI tools.

Collect and Organize Data

Next, specialists gather data from different parts of your supply chain. Stuff like old sales info, customer details, stock records, and delivery stats. They even consider outside factors, like market trends.

Data Preparation and Cleaning

There are often errors, inconsistencies, or missing values in the raw data, which can hinder the performance of AI algorithms. Furthermore, implement data cleaning and preparation procedures to address these issues, including eliminating duplicates, correcting errors, dealing with missing data, and providing proper data formatting training for AI models.

AI Algorithm Selection

Based on your defined goals and the nature of your supply chain data, choose the appropriate AI algorithms and technologies. This can be regression, classification, clustering, or deep learning techniques for complex pattern recognition.
Additionally, look for relevant AI technologies, such as automatic robotic systems, computer vision, natural language processing, machine learning, or predictive analytics, that match your goals.

Choose the right technology stack

During this phase, supply chain data analysis software development experts will help you choose AI tools and techniques that match your goals and available data This may include identifying the right AI technologies, such as robotic process automation, computer vision, natural language processing, machine learning, or predictive analytics.

Data Modeling

Data modelling is an important process that requires the selection of appropriate machine learning algorithms. Our team of data scientists experiments with manipulating data sources and creating features that can better explain variations in the data. This means your organization can leverage the power of algorithms like Seq-Seq and Auto-Encoders to make predictions.
However, it is important to note that all AI algorithms are based on specific mathematical assumptions. Thus, it is necessary to prepare the data in a particular way to satisfy these assumptions.

Integrate with Existing Systems

Now, experts will add the power of AI in the supply chain to the services and technologies that drive your supply chain. To do this, it may be necessary to link enterprise resource planning (ERP), warehouse management (WMS), logistics management (TMS), or other related software to an AI model. Experts will verify the system integration is easy and allows for data transfer.

Test and Validation

In this phase, experts put your AI models and connected systems in place through thorough testing and validation.
However, by comparing predictions or recommendations with actual results, you can confirm the accuracy, reliability, and efficiency of AI algorithms. Based on the test results, QA specialists iterate and optimize the models.

Testing and Deployment

Testing and implementation for a small business is highly recommended before implementing AI in the supply chain. This approach allows them to critically assess the AI system, identify any issues or areas for improvement, and optimize the programs.
By doing so, AI/ML experts ensure your AI wins for supply chain optimization and implementation. They take the necessary steps to test your AI for supply chain solutions and use a flexible supply chain.

Continuous Improvement

Continuous improvement is about constant monitoring and improving the app’s performance and quality. Specifically, this includes gathering user reviews, data analysis, product testing, and frequent app updates.
Furthermore, when it comes to development, Continuous improvement means you will continue to monitor the app in different markets.

Case study


Embracing the transformative power of artificial intelligence (AI), Appvin Technologies is at the forefront of supply chain transformation. As businesses navigate complex global markets and dynamic customer needs, AI in the supply chain is working as a catalyst for unprecedented efficiencies, agility and innovation.

Challenges & Problems

Furthermore, in partnership with Supply Chain Management, Appvin faced the challenge of creating AI-powered mobile apps to meet various needs. The main obstacle was integrating complex AI algorithms into apps and ensuring seamless operation across platforms.


However, to overcome this, Appvin Technologies used a collaborative approach to tackle­ this challenge. It formed a solid relationship with the client, mastered their requirements, and progressively polished the AI model.


Robust mobile apps came to life as a result, bringing noticeable upgrades in supply chain performance. The outcomes highlighted more accurate demand predictions, less maintenance downtime, smooth logistics operations, better supply chain visibility, customer satisfaction, and increased customer happiness. AppVin, showing innovation and persistence, proudly showcased how AI can bring groundbreaking changes to supply chain management.


In conclusion, the benefits of AI in supply chain management are inescapable. With widespread adoption by companies of all sizes and shapes, AI is a trending supply chain technology among businesses. Given the current scenario, any supply chain business needs to integrate with supply chain AI solutions for better quality.

However, Appvin's data analytics services help you extract valuable insights from your business data to scale. Contact our team of industry professionals to explore and dive deeper into the benefits of AI for your supply chain business

Last Updated in May 2024

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Henk Kooijman

Henk Kooijman, the Managing Director of AppVin Technologies, a software development company based in the Netherlands, leads a team of highly skilled developers who deliver top-notch software solutions across various platforms. This firm is recognized as one of the top software development companies by leading research platforms. Kooijman regularly contributes his expertise to prominent blogging sites within the industry.