10 AI ML In Supply Chain Management Trends To Look Out For In 2024

AI in supply chain management was one of the most searched terms on our website – AiThority.com. In addition to AI in supply chain management, readers also looked up keywords such as Robotic Process Automation, Deep learning, AI ML analytics, and computer vision to discover new articles and news. Why is AI in supply chain management such a popular trend? We found three main reasons for pushing the numbers in the industry:

Digital Automation at its Peak

In the last 5 years, businesses have identified AI in supply chain management as a key technology to accelerate digital transformation. AI solutions can handle 99% of modern digital automation processes, saving organizations millions of dollars per day in revenue, and 6500+ hours in productivity. AI technology for logistics, transportation, and supply chain inventory management can also simplify complex jobs, which results in faster delivery of material, better service quality, and improved workforce optimization across locations.

Intelligent Data to Forecast Trends

Predictive analytics in supply chain management help users stay ahead of the competition. Most AI users include AI-led predictive intelligence to enhance the operational efficiencies of their existing forecasting platforms. In today’s fast-changing landscape, AI’s intelligent data analytics streamline numerous processes, including inventory management, demand forecasting, transportation planning, fraud detection, climate predictions, workplace quality, risk mitigation, and overall decision-making processes.

IoT and Connectivity

Supply chain companies with AI foundational models are found to be better prepared to embrace the Internet of Things (IoT), 5G, and sensors-driven operations. Adding AI to supply chain management can be a lengthy, expensive, and complex process. However, organizations with a long-term AI vision can run intelligent processes and applications using on-premise, hybrid, and cloud-based platforms without blowing their annual budgets. According to Oracle, AI-powered supply chain management (SCM) tools enhance visibility and traceability for manufacturers and suppliers as they interconnect globally in real time to track vast quantities of supplies and workers ethically.

Winners and Game-changers of AI in the Supply Chain Management Industry

Top AI and ML solutions for supply chain include AWS Supply Chain, Google Cloud Vertex, Microsoft Supply Chain Platform & IBM Watson.

If you remember the historic moment of 2016, DeepMind’s AlphaGo, a machine, upset 18-time world Go game champion Lee Sedol, a complicated board game requiring intuition, imagination, and strategic thinking—abilities long regarded as fundamentally human. Since then, advancements in artificial intelligence (AI) technology have led to widespread disruption across many sectors.

Through data analysis, AI can reliably estimate future demand, allowing businesses to maximize stock while simultaneously decreasing the likelihood of stockouts and streamlining supply chain operations.

Read: How to Incorporate Generative AI Into Your Marketing Technology Stack

The Role of AI in the Supply Chain In 2022, the market was at $3.34 billion, and forecasts project that by 2029, it will have grown to generate about $46.15 billion in sales.

An Overview of the Modern Supply Chain Management (SCM)

As a result of advancements in technology and the introduction of novel components, supply chains have gotten more intricate in recent years. That’s why resilient supply chain operations necessitate cutting-edge approaches to managing these challenges. Artificial intelligence (AI) and automation, supply chain as a service (SaaS), circular supply chains (CS), risk management (RM), stability (ST), and a heightened emphasis on sustainability (Sustainability) are now the most prominent developments in SCM.

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Managing the production and distribution of inputs, intermediates, and outputs is what supply chain management (SCM) is all about. Everything from manufacturing to packaging to delivery is part of this process.

Expert Insights on Supply Chain

This insight has been contributed by Doug Gray, Chief Technology Officer, Amazon Business.

Procurement teams will embrace the AI wave: As AI tools become more prominent and accessible in 2024, organizations will invest in analytics and insights tools, automation, and AI-driven optimization of purchasing decisions to improve efficiency. Over the next few years, procurement decision-makers will also learn and invest in new digital tools that could scale up their procurement operations. These investments will not only reduce manual work and allow departments to spend less time on tasks that can be consolidated or automated, but they will also reduce spending, streamline processes, and ensure organizations meet employee and stakeholder needs.

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SCM Components

• Management of the entire flow of goods and services to and from a business

• Overseeing the movement of all the materials, finished goods, and processes that come together to get products to customers

• Actively managing supply chain activities to maximize customer value and achieve a sustainable competitive advantage

• Managing the movement of materials, information, and money is all part of supply chain management. From manufacturing to the final mile of distribution, everything in the supply chain is included.

• With good SCM, firms can employ capex assets, such as production or transportation equipment, most effectively. For example, firms may manufacture to the requirement rather than adding wear and tear on industrial equipment needlessly.

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Which companies use AI in the supply chain?

• Siemens
• Dataiku
• SAS Machine Learning
• Databricks
•  OCI AI Services (Oracle)
• SAP Integrated Business Planning (IBP)
• Coupa.
• Epicor.
• Echo Global Logistics.
• Infor.
• Covariant.
• Zebra Technologies.
• HAVI.

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Will AI take over supply chain management?

With the support of IBM’s Adobe consulting services, you can streamline your company’s content supply chain, which will lead to shorter time-to-market, lower costs, and more productivity. Together with Adobe, IBM has begun a marketing transformation journey to drastically streamline the company’s marketing department from beginning to finish. Because they are already undertaking this work in-house, IBM and Adobe have come up with a value proposition to optimize the content supply chain. We are referring to this as “Client Zero.”

Supply chains may be optimized by today’s AI, which can even personalize them so that the appropriate product is delivered to the right consumer at the right price. However, few businesses are prepared for the kind of data exchange that would be required to achieve this. 

Top 10 Supply Chain Trends For 2024

1. Supply Chain as a Service (SCaaS)

   AI and ML will continue to play a crucial role in providing real-time visibility into supply chain operations. This includes tracking shipments, monitoring inventory levels, and predicting disruptions.

   The increasing complexity of value chains makes it extremely difficult to perform all of your supply chain procedures in-house. Skilled manipulation and maintenance will become necessities as we transition from manual to digital processes, use vast numbers of IoT-enabled devices, analyze data, and perform routine maintenance.

   Many organizations won’t have the required skills to carry out these jobs and will outsource many of these vital procedures.

   Better customer service, more productivity, and cheaper expenses are all results of using SCaaS. SCaaS offers comparable services with supply chain-centric benefits, such as improved asset management. In the face of a global epidemic, the ability to adapt quickly and easily stands out as a significant benefit.

2. Demand Forecasting and Inventory Optimization: AI-powered demand forecasting models will become more accurate, enabling companies to optimize their inventory levels, reduce carrying costs, and improve overall supply chain efficiency. Constant product shipping calls for more money but creates logistical headaches. Smaller problems, such as vehicle maintenance, become increasingly important to prevent when demand is consistently high.

   In periods of high demand, the loss of even one truck can have catastrophic effects on the supply chain. Keeping track of corporate operations in a flexible manner that can adapt to market shifts will be more critical than ever. Investment in manufacturing software will be necessary for truckmakers to automate operations and save costs. Stronger supply chain cooperation mechanisms may be necessary for shippers and transportation businesses to adapt to an otherwise reasonably steady environment.

3. Predictive Maintenance: ML algorithms will predict equipment and vehicle maintenance needs, reducing downtime and ensuring that logistics operations run smoothly. 

4. Route Optimization: AI will help optimize transportation routes, taking into account real-time traffic data, weather conditions, and other variables to minimize costs and delivery times.

5. Supplier Risk Management: AI will be used to assess and predict supplier risks, allowing companies to diversify their supplier base and develop contingency plans to mitigate disruptions.

6. Blockchain for Transparency: While not AI or ML per se, blockchain technology, when combined with AI, can enhance transparency and traceability across the supply chain, reducing fraud and errors. With blockchain’s rising popularity, it only makes sense to follow the need for more supply chain transparency. The decentralized nature of the data stored in a blockchain makes it an ideal platform for creating fully transparent supply chains. Before we go any further, let’s define blockchain.

   Blockchain makes use of data in pieces or “blocks,” whereas traditional databases use tables to organize their data. When the capacity of these storage blocks is reached, more blocks are produced and appended to the end of the chain to make room for additional data. These blocks, when combined, create immutable records that accurately date and time stamp all user transactions, providing invaluable transparency. 

7. Autonomous Vehicles and Drones: The use of autonomous vehicles and drones in logistics will increase, with AI and ML algorithms powering navigation, route planning, and cargo handling.

8. Warehouse Automation: AI-driven robots and automation systems will continue to transform warehouses, improving order picking, packing, and inventory management processes. Given these benefits, it’s not hard to imagine the global robots industry growing from $55.8 billion in 2022 to $91.8 billion in 2026.

   Robotics vendors may now safely activate and integrate their products with your operations without ever having to send an employee to your facility. Automation holds a fair, connotation for scooping up employment. It’ll handle the mundane stuff so you can concentrate on the important stuff. Managers may avoid layoffs by investing in their present staff members’ growth in knowledge and expertise. Companies providing WMS (warehouse management systems) may make more of an effort to guarantee their products are compatible with AMR systems as a result of this approach.

9. Natural Language Processing (NLP) for Customer Service: AI-driven chatbots and virtual assistants will enhance customer service and communication within the supply chain, addressing inquiries and resolving issues efficiently.

10. Sustainability and Green Supply Chains: AI and ML will be used to optimize supply chains for sustainability, reducing carbon footprints, and minimizing waste through better routing and materials management.

 Please note that the field of AI and ML is evolving rapidly, and new trends and technologies will likely emerge in supply chain management by 2024. To stay updated, it’s essential to keep an eye on industry publications, attend conferences, and actively engage with experts and professionals in the field.

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Q. How does analytics affect supply chain optimization?

A. Analytics plays a crucial role in supply chain optimization because it enables decision-makers to make more informed choices based on collected data and insights. The following are some of analytics’ most vital contributions to optimizing supply chains:

• Demand forecasting
• Inventory management
• Supply network optimization
• Risk management
• Performance measurement

Q. How are AI and ML applicable in the supply chain?

A. State-of-the-art algorithms facilitate the integration of AI and ML into the supply chain ecosystem. Artificial intelligence’s contribution to supply chain solutions will be to improve data quality while also providing a fresh perspective on the logistics process.  It can also aid in forecasting demand and restocking at optimum levels quickly.

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Q. What are some examples of AI and analytics in the supply chain?

A.

• Demand forecasting
• Warehouse automation
• Route optimization
• Supply chain risk management
• Predictive maintenance
• Supplier management
• Real-time supply chain visibility

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Q. What is the future of AI in SCM?

Companies in the supply chain are shifting their attention from products to results, which means that the old ways of doing business will become antiquated and eventually obsolete, leaving in their wake the corpses and names of the losers. As the foundations of global supply networks grow stronger, competitive pressures will push businesses to squeeze every last cent out of their operations.

This is especially true for small and medium-sized businesses (SMEs) since they lack the resources of larger corporations in terms of technological and operational expenditures, currency hedging options, and market concentration. In such cases, looking at and embracing the winning SaaS and cloud solutions is a strategy for keeping up, and getting ahead of, the international conglomerates.

Artificial intelligence (AI) algorithms and location technology tools can sift through mountains of data, industry trends, and customer behavior to forecast future demand with greater precision. As a result, businesses may better manage their inventories, have fewer stock-outs, and boost customer satisfaction.

Last but not least

Businesses operating in the supply chain face several new problems and technological opportunities in the years ahead. Businesses will begin to focus on supply chain resilience to overcome unanticipated interruptions. Technology, such as digital supply chain twins, robots, AI, and automation, may be used to assist in maintaining skill, adaptability, and scalability.

The blockchain will become the center of attention and reveal hitherto hidden business operations. Supply chain as a service (SCaaS) is expected to expand with the market for cloud-based technologies.