Global Artificial Intelligence in Supply Chain Market Research Report: Forecast (2022-27)

Market Definition

Artificial Intelligence is the simulation of human intelligence displayed by machines, where machines can be utilized for problem-solving, learning, or even making decisions. In addition, supply chain management solutions based on AI provide visibility & scalability into warehouse operations, logistics channels, and resource management, among others, through the ability to analyze a massive volume of data. It has numerous benefits, such as accurate inventory management, warehouse efficiency enhancement, and reduced operational costs. Therefore, the increasing demand for AI-based services during warehouse operations would considerably escalate the market growth in the coming years.

Market Insights

The Global Artificial Intelligence in the Supply Chain market is anticipated to grow at a CAGR of around 37.89% during the forecast period, 2022-27. The factors responsible for the market growth are the increasing adoption of AI-based services in warehouse automation for improving accuracy & security, the rising count of AI-based technology start-ups, and the dire need for automating supply chain routes, among others. Additionally, the vast pool of data collected by the operational tasks in the warehouses has augmented the use of AI-driven tools which would help the facility owners to improve inventory management efficiency, thereby enhancing productivity.

Furthermore, the low demand of the goods may lead to a stockpile of unsold stocks in the warehouses, which increases the burden of maintaining it. Therefore, demand forecasting through AI integration can help organizations to manufacture products accordingly & accurately with minimum waste of goods. This is mainly important during a global supply chain crisis, which was felt during the COVID-19 pandemic. Also, the application of AI for time-series forecasting helps an organization in planning the inventory & logistics based on the insights derived from the seasonal sales cycles.

Moreover, data such as previous sales history, macroeconomic situations, product reviews, and sales promotions, among others, is fed into the AI model to find the last year’s data. Therefore, the trained AI model has the ability to provide demand estimates during the forecast period. In addition, modern AI algorithms such as Long Short-term Memory networks (LSTMs) & autoencoders have proved to help generate new product information forecasts. Thus, the expanding AI algorithms for forecasting demand & supply globally have bolstered the need for AI in the supply chain during the forecast period.

Key Trend in the Market

• Increasing Demand for Intelligent Business Processes & Automation to Escalate the Market Growth

Due to the rising need for a variety of warehouse automation operations, businesses, including IBM & Amazon Web Services (AWS), among others, have created a supply chain intelligence suite with an integrated suite that offers AI-based supply chain optimization & automation solutions. These solutions improve supply chain processes, increase agility, and optimize warehouse operations. Furthermore, an intelligent automation system is made to encourage cooperation by fusing disparate data sets to help you produce actionable insights, smarter workflows, and intelligent automation, which leads to quicker problem-solving & more effective supply chain operations. Therefore, the growing technological advancement globally would propel the demand for AI in the supply chain in the coming years.

Impact of Industry 4.0 on the Global Artificial Intelligence in the Supply Chain Market

The industrial 4.0 revolution catalyzed the development of new automation technologies, robotics, Internet of Things (IoT), Big data, machine learning (ML), artificial intelligence, as well as for analytics, which has resulted in the rapid adoption of technology in the warehouse operations. Therefore, with the advent of Industry 4.0, supply chain mechanisms are transforming by adopting digitization, automation, and centralized business intelligence systems. Notably, these technologies mainly depend on cloud computing to bring agility in services & quicker response.

Furthermore, the incorporation of AI & IoT in industrial activities is changing the pace of the transformation in supply chain management (SCM). As a result, the development in the supply chain is visible at every level of manufacturing, procurement, logistics, warehousing, and fulfillment, which has made companies with integrated digital supply chain functions far more efficient than their predecessor.

Market Segmentation

Based on the Application:

• Fleet Management
• Supply Chain Planning
• Warehouse Management
• Virtual Assistant
• Machine Utilization
• Others (Risk Management, Freight Brokerage, etc.)

Here, Warehouse Management gained notable traction during the historical period. Some crucial factors for the segment growth are the emerging need for efficient warehousing has mandated the deployment of cutting-edge technologies in the facilities to ensure optimum supply chain routes, inventory management, and timely delivery of goods to the end consumer. The incorporation of Artificial Intelligence (AI) for warehouse management helps facilitate redundant tasks with greater efficiency, hence increasing productivity.

Furthermore, during the COVID-19 period, the disruption caused by the abrupt halt in the global supply chain has compelled the facility owners to incorporate technologies, such as AI, etc., to direct their supply chains with the least amount of errors by streamlining complex procedures. Hence, results in the proliferation of the market growth in the upcoming years.

Based on Technology:

• Machine Learning
  • Supervised Learning
  • Unsupervised Learning
  • Reinforcement
• Natural Language Processing (NLP)
• Context-aware Computing
• Deep Learning
• Computer Vision

Among them, Machine Learning acquired a noteworthy share in the Global Artificial Intelligence in the Supply Chain market during 2017-21. The complex machine learning (ML) algorithms result in radical efficiencies in the supply chain. Therefore, based on the data gathered from the vast pool of transactions in the supply chain network assists in inventory forecasting, and price planning, among others. Moreover, machine learning has numerous benefits ranging from risk mitigation to cost savings through reduced operational redundancies to enhanced supply chain forecasting & speed up deliveries through more optimized routes to enhance customer service.

In addition, AI for supply chain optimization is being preferred by several manufacturers globally, therefore several technology providers have managed to grab the opportunity & launched their products strategically in the market. This is expected to pave strong grounds for AI in the Supply Chain market in the forthcoming years.

Based on End-User

• Automotive
• Aerospace
• Retail
• Food & Beverages
• Others (Healthcare, Energy, etc.)

Of them all, the rising investments in the Retail sector have emerged as the major demand generator for AI solutions in the supply chain. Retailers can use Big Data & AI to analyze past purchase patterns & necessities during the festive seasons, as well as current purchasing behavior, to predict which products will be in demand in the future. Additionally, by having a better understanding of the status of various activities like purchase orders, shipments, and inventory reports, retailers may increase product availability & scalability, which will raise consumer satisfaction.

Eventually, retailers are equipped with better & more accessible real-time data to ensure product availability on their shelves. Therefore, AI-based solutions elevate customer satisfaction levels & contribute to improved downstream sales in the retail industry. This has escalated the requirement for AI algorithms, which could enhance the product availability process & transform the products that are created, sourced, and sold through retailers.

Based on Deployment Type:

• On-Premise
• Cloud

Among the two, the Cloud Deployment Type acquired a considerable share in the Global Artificial Intelligence in the Supply Chain market during the historical period due to the increasing adoption of cloud services by the Small & Medium Enterprises (SMEs). Further, the companies have been inclined toward cloud-based services & provide digital transformation services to attain high scalability & cost-efficiency.

In addition, the cloud-based deployment offers quick & real-time access to data that helps in enhancing customer satisfaction. Furthermore, the cloud reduces IT expenditure by removing the costs associated with purchasing, managing, and maintaining on-premises hardware & application infrastructure, which would further contribute to the market's growth.

Regional Landscape

Geographically, the Global Artificial Intelligence Market expands across:

• North America
• South America
• Europe
• The Middle East & Africa
• Asia-Pacific

Of all the regions globally, North America witnessed a significant growth rate in the Global Artificial Intelligence in the Supply Chain market during the historical period. This is due to the presence of emerging economies focusing on improving supply chain solutions & the presence of major market players in the region. Furthermore, regional countries such as the US, Mexico, and Canada have a high inclination for the adoption of advanced technologies such as AI, ML, IoT, and cloud computing in supply chain management, resulting in escalating the demand for AI-based services for various warehouses operations.

In addition, the sizeable data collected by the operational tasks in the warehouses have augmented the use of AI-driven tools, which would help the owners to improve the effectiveness in inventory management that would later enhance productivity & scalability. Therefore, the growing technological advancement in warehouse operations is expected to drive AI-based services in the Supply Chain market during 2022-27.

Recent Developments by the Leading Companies

• In 2022, FedEx & Microsoft Corporation extended their partnership to offer ‘logistics as a service,’ to help businesses better fulfill, ship, and serve customer orders. In addition, the company started producing logistics solutions using data & AI in order to make deliveries more efficient.
• In 2020, BMW started working with Nvidia Corporation to advance AI in logistics. The company provides logistics robots with high-performance computer technology across various vehicle-making operations.

Market Dynamics:

Key Drivers: Increasing Demand for Warehouse Automation Solution

The increasing demand for warehouse automation for various applications such as robotics, computer vision, and language processing tools to streamline warehouse operations led to the increased demand for Artificial Intelligence (AI) in recent years. In addition, there are several benefits of using AI in warehouse automation such as to improve productivity, increase accuracy, and enhancement of security, which would result in increased demand for AI in warehouse operations in the coming years.

Furthermore, using AI solutions result in a reduction of errors in warehouse operations. AI robots can wisely understand the warehouse environment, thus improving the accuracy of placing items & recovering them when required. In addition, warehouses utilize various technologies such as IoT, computer vision, and AI that helps to improve the accuracy during warehouse operations. Hence, the rising demand for warehouse automation solutions resulted in escalating the demand for AI-based services in the supply chain.

Possible Restraint: Additional Cost of Training IT Personnel to Hinder the Market Growth

The increased expense incurred throughout the training process adds to the buyer's financial burden and could impede market expansion. New technologies such as AI, Machine Learning, and Natural Language Processing require training & background of technical know-how that again needs impressive investment in terms of time & money. Therefore, small- & medium-scale retailers are deterred from investing their resources, hence further hindering the market growth.

Key Questions Answered in the Market Research Report:

1. What are the overall statistics or estimates (Overview, Size- By Value, Forecast Numbers, Segmentation, Shares) of the Global Artificial Intelligence in the Supply Chain Market?
2. What are the region-wise industry size, growth drivers, and challenges?
3. What are the key innovations, opportunities, current & future trends, and regulations in the Global Artificial Intelligence in the Supply Chain Market?
4. Who are the key competitors, their key strengths & weaknesses, and how do they perform in the Global Artificial Intelligence in the Supply Chain Market based on the competitive landscape?
5. What are the key results derived from surveys conducted during the Global Artificial Intelligence in the Supply Chain Market?