Cognitive Supply Chain Market Size, Share & Trends Analysis Report By Deployment (Cloud, On-Premise), By Enterprise Size, By Automation Used (IoT, Machine Learning), By Industry Verticals, By Region, And Segment Forecasts, 2023 - 2030

Report Overview

The global cognitive supply chain market size was valued at USD 7.23 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of 15.4% from 2023 to 2030. The market is on track for significant growth due to technological advancements and evolving business needs. Supply chain systems have grown more complex and data-driven because of the rapid progress of AI technologies such as machine learning and natural language processing. This enables businesses to employ predictive analytics and demand forecasting to optimize inventory management and keep the supply chain running smoothly. In addition, including Big Data and Internet of Things (IoT) devices in supply chain operations has resulted in vast amounts of data. Cognitive technology can process and analyze this data in real time, providing valuable insights that lead to better decision-making and operational efficiency.

The rise of customer-centricity as a core business strategy has also been a driving force behind the adoption of cognitive supply chain solutions. Businesses now strive to deliver a superior customer experience by streamlining processes and reducing lead times. Cognitive technologies help achieve this by optimizing operations, ensuring products reach customers promptly, and improving overall supply chain responsiveness. Cost optimization remains a significant factor in driving the growth of this market. Businesses can achieve significant cost savings by minimizing inventory holding costs, reducing transportation expenses, and enhancing overall supply chain efficiency.

This cost-effectiveness makes cognitive supply chain solutions attractive for companies seeking to stay competitive in today's dynamic market landscape. The increasing adoption of cognitive technologies is not limited to a specific industry but is observed across various sectors. As more companies witness the tangible benefits of cognitive supply chain solutions, the market is expected to experience higher adoption rates. This growing interest and acceptance of cognitive technologies will likely further fuel the market's expansion.

COVID-19 Impact on the Cognitive Supply Chain Market

The COVID-19 pandemic significantly impacted the market, reshaping how businesses approached supply chain management. One of the most notable effects was an increased demand for supply chain resilience. The pandemic exposed vulnerabilities in global supply chains, resulting in widespread disruptions and shortages. As a response, businesses recognized the urgent need to build more robust and agile supply chains that could withstand future disruptions. Cognitive technologies like AI and machine learning became vital tools in predicting disruptions, optimizing inventory management, and enhancing overall supply chain visibility and resilience. Moreover, the pandemic accelerated the digital transformation of supply chain operations. As companies shifted to remote work and faced operational challenges, there was a heightened emphasis on automation and cognitive technologies. Organizations that had already adopted AI-driven supply chain solutions were better equipped to manage the sudden changes and mitigate the impact of disruptions. The pandemic acted as a catalyst, driving businesses to explore and embrace technologies that could improve supply chain efficiency and decision-making.

In the face of uncertainty caused by the pandemic, demand forecasting became particularly challenging. With shifting consumer behaviors and demand patterns, accurate forecasting was critical for inventory planning and optimization. Here, AI-powered predictive analytics played a crucial role in providing businesses with valuable insights into customer demand patterns, enabling them to make informed decisions and adapt to rapidly changing market conditions. Health and safety concerns also came to the forefront during the pandemic, impacting supply chain operations. Cognitive technologies played a role in optimizing warehouse layouts, automating tasks to reduce human interaction, and ensuring adherence to safety protocols. By incorporating AI into safety measures, businesses aimed to protect their workforce while maintaining operational continuity.

Deployment Insights

In terms of deployment, the market is classified into cloud and on-premise. The on-premise deployment segment dominated the overall market, gaining a market share of 68.3% in 2022 and witnessing a CAGR of 14.8% during the forecast period. The preference for on-premise deployment in the market can be attributed to several factors. One primary consideration is data security. Companies dealing with sensitive supply chain data, such as those in the healthcare or defense sectors, often have stringent data security and compliance requirements. Opting for on-premise deployment allows them to maintain direct control over their data, reducing the risk of data breaches and ensuring compliance with industry-specific regulations. Moreover, data privacy concerns play a significant role in driving the demand for on-premise deployment. Organizations can exercise greater control over data privacy by hosting cognitive supply chain solutions on their own servers or data centers, minimizing the exposure of sensitive information to external entities.

The cloud deployment segment is anticipated to witness a faster growth, growing at a CAGR of 16.6% throughout the forecast period. One of the primary reasons cloud deployment's rising popularity in the market is its scalability. Cloud-based solutions allow businesses to adjust their resources based on demand fluctuations and evolving business needs. As supply chain operations often vary seasonally or due to changes in market conditions, the cloud provides a dynamic infrastructure that can efficiently handle varying workloads without significant reconfiguration. Cost-effectiveness is another compelling advantage of cloud deployment segment. Companies can significantly reduce their initial capital expenditure by eliminating the need for substantial upfront investments in hardware and infrastructure. Rather, they can go for a pay-as-you-go model, where they only pay for the computing resources they use. This cost-effective approach can appeal to businesses seeking to adopt cognitive technologies while managing their budget efficiently.

Enterprise Size Insights

In terms of enterprise size, the market is classified into SMEs and large enterprises. Among these, the large enterprises segment is expected to dominate in 2022, gaining a market share of 68.9% and witnessing a CAGR of 15.1% during the forecast period. Large enterprises were leveraging cognitive technologies to enhance their supply chain capabilities in several key areas, such as demand forecasting, inventory management, logistics optimization, and supplier relationship management. By integrating AI and ML into their supply chain processes, these enterprises could gain deeper insights from vast amounts of data, identify patterns, and make more accurate predictions. Adopting cognitive technologies also improved efficiency, reduced operational costs, and minimized disruptions in supply chain activities. For instance, real-time monitoring of supply chain data enabled companies to proactively address potential bottlenecks, mitigate risks, and respond swiftly to changes in demand or supply. Furthermore, large enterprises were increasingly partnering with tech companies and specialized AI providers to implement cognitive supply chain solutions tailored to their specific needs. Such collaborations allowed them to access cutting-edge technologies and expertise, speeding up the implementation process and yielding more substantial benefits.

The SME segment is anticipated to observe significant growth, growing at a CAGR of 16.0% throughout the forecast period. One key factor contributing to the growth of the SME enterprise segment in the market is cost-effectiveness. SMEs can now access cloud-based cognitive supply chain platforms that require lower upfront investment than traditional on-premises solutions, making them more feasible for smaller budgets. This reduced financial barrier has opened up opportunities for SMEs to adopt innovative technologies and gain a competitive edge in their respective industries. Moreover, the scalability of cognitive supply chain solutions has been another driving force behind SME adoption. Many providers of these solutions offer flexible packages that allow SMEs to start with a small-scale implementation and expand as their business grows. This approach aligns well with the dynamic nature of SMEs, as they often experience fluctuating demands and changing business requirements. With the ability to scale their cognitive supply chain operations, SMEs can adapt more effectively to market demands and seize new growth opportunities.

Automation Used Insights

In terms of automation used, the market is classified into the Internet of Things (IoT), Machine Learning (ML), and others. The Internet of Things (IoT) segment is expected to dominate in 2022, gaining a market share of 44.5% and witnessing a CAGR of 15.6% during the forecast period. One of the primary drivers behind adopting IoT automation in the market is the promise of significant cost savings and operational efficiency gains. Companies can streamline their operations and reduce unnecessary expenditures by automating various aspects of the supply chain, such as inventory management, asset tracking, and order processing. This improved overall efficiency and a more cost-effective supply chain management approach. Integrating IoT devices and cognitive technologies also offers enhanced visibility and transparency across the supply chain. With real-time data collection and analysis, businesses gained valuable insights into the movement and condition of goods at each stage of the supply chain. This unprecedented visibility allowed companies to proactively identify bottlenecks and potential issues, leading to better decision-making and optimized processes.

The Machine Learning (ML) segment is anticipated to witness the fastest growth, growing at a CAGR of 16.4% throughout the forecast period. ML automation in the market segment allows businesses to streamline and optimize their supply chain processes, reduce operational costs, improve efficiency, and make data-driven decisions. By automating repetitive tasks, analyzing vast amounts of data, and identifying patterns and insights, ML-driven solutions can help companies gain a competitive edge in the market. The growth of ML automation in the market can be attributed to several factors. Firstly, AI and ML adoption is increasing as businesses recognize the potential benefits of these technologies in supply chain management. Companies have embraced these solutions to gain better control over their supply chain, enhancing performance and improving customer satisfaction. Secondly, advancements in ML algorithms have been instrumental in driving the growth of automation in the segment. Ongoing research and development have led to more sophisticated ML algorithms capable of handling complex supply chain challenges, making automation more effective and reliable. These advanced algorithms can process vast amounts of data quickly and accurately, enabling businesses to make more informed decisions.

Industry Verticals Insights

In terms of industry verticals, the market is classified into manufacturing, retail & e-commerce, logistics & transportation, healthcare, food & beverage, and others. Among them, the manufacturing segment is expected to dominate in 2022, gaining a market share of 33.6% and witnessing a CAGR of 14.7% during the forecast period. One of the key factors of growth is predictive maintenance. Manufacturers increasingly integrated cognitive technologies to implement predictive maintenance strategies. By analyzing real-time data from sensors and equipment, they can predict potential failures and perform maintenance before breakdowns occur. This proactive approach reduced unplanned downtime and extended the lifespan of critical machinery, contributing to improved operational efficiency. Quality control and defect detection are also areas witnessing notable advancements in the manufacturing industry by integrating cognitive supply chain solutions. AI algorithms were utilized to identify defects and deviations during the production process, leading to higher product quality and reduced waste. This enhanced quality control played a crucial role in ensuring customer satisfaction and maintaining the brand reputation of manufacturers.

The logistics & transportation segment is anticipated to witness the fastest growth, growing at a CAGR of 17.5% throughout the forecast period. One significant advancement in this market is the emergence of autonomous vehicles, including trucks, drones, and delivery robots. These vehicles leverage cognitive capabilities such as computer vision and machine learning algorithms to navigate traffic, identify obstacles, and optimize routes for efficient and safe deliveries. Another key development is the widespread adoption of predictive analytics. Logistics companies can anticipate demand fluctuations, identify potential disruptions, and optimize inventory levels by harnessing data from various sources like IoT devices, sensors, and weather forecasts. This results in reduced costs and improved service levels. Furthermore, implementing blockchain technology has enhanced transparency, traceability, and security throughout the supply chain. Cognitive capabilities complement blockchain by automating data verification, ensuring records' accuracy, and strengthening supply chain management. Cognitive robotics has also played a crucial role in the logistics and transportation industry. These robots can handle complex tasks, adapt to dynamic environments, and collaborate with human workers, improving warehouse efficiency and order fulfillment. Natural Language Processing (NLP) has facilitated better communication within the supply chain. Voice-enabled interfaces and chatbots allow users to interact with supply chain systems intuitively, enhancing data entry, tracking, and issue resolution processes.

Regional Insights

North America led the overall market in 2022, with a market share of 31.2%. One of the primary factors contributing to expanding the market in North America is the increasing demand for efficiency and cost savings. Companies actively seek ways to streamline their supply chain operations, reduce expenses, and enhance productivity. Cognitive supply chain solutions allowed them to identify patterns, predict demand, and optimize inventory and logistics processes, to improve resource allocation and reduce waste. Moreover, the proliferation of big data and analytics played a pivotal role in driving the adoption of cognitive supply chain technologies. With the exponential growth of data from various sources, such as IoT devices, sensors, and transactional systems, businesses could leverage advanced analytics and AI techniques. These solutions could process vast amounts of data and derive valuable insights, enabling better decision-making and more informed strategic planning.

Asia Pacific is anticipated to observe significant growth, growing at a CAGR of 17.0% throughout the forecast period. The Asia Pacific market has witnessed substantial growth over the past few years, driven by a convergence of technological advancements and a burgeoning demand for efficient supply chain management solutions. With the region experiencing robust economic growth and rapid digital transformation across industries, businesses have been eager to optimize operations and reduce costs. As a result, adopting artificial intelligence (AI) and cognitive computing in supply chain management has become increasingly prevalent. One of the key factors contributing to this growth is the increasing need for efficiency in supply chain operations. As markets become more competitive and customer expectations rise, companies are under significant pressure to streamline their supply chain processes and improve responsiveness. Cognitive technologies offer advanced analytics and decision-making capabilities, empowering businesses to make data-driven, real-time decisions, thereby enhancing overall efficiency.

Key Companies & Market Share Insights

The cognitive supply chain market is fragmented and is anticipated to witness competition due to several players' presence. Some of the leading companies globally included in the study are IBM Corporation; Oracle; Amazon.com; Accenture plc; Intel Corporation; NVIDIA Corporation; Honeywell International Inc.; C.H. Robinson Worldwide, Inc.; Panasonic; and SAP SE, among others. To capture a greater market share, the key market players adopting strategies such as entering into collaboration and engaging in mergers & acquisitions of other cognitive supply chain companies.

In October 2022, Oracle introduced new product innovations for its data and analytics solutions. With Oracle Fusion Analytics, decision-makers can access over 2,000 prebuilt KPIs, dashboards, and reports across CX, HCM, ERP, and SCM analytics to monitor performance against strategic goals. The latest Oracle Analytics Cloud enhancements aim to boost business users' productivity by reducing their reliance on IT while benefiting from curated data assets and a centralized semantic model. Adding advanced composite visualizations and AI/ML enhancements extends ML capabilities, including Oracle Cloud Infrastructure cognitive services like AI Vision for processing visual information. Some of the prominent players in the global cognitive supply chain market include:

• IBM Corporation

• Oracle; Amazon.com

• Accenture plc

• Intel Corporation

• NVIDIA Corporation

• Honeywell International Inc.

• C.H. Robinson Worldwide, Inc.

• Panasonic; SAP SE

Cognitive Supply Chain Market Report Scope

Global Cognitive Supply Chain Market Report Segmentation

This report forecasts revenue growths at global, regional, and country levels and provides an analysis of the industry trends in each of the sub-segments from 2019 to 2030. For this study, Grand View Research has segmented the global cognitive supply chain market based on deployment, enterprise size, automation used, industry verticals, and region.

• Deployment Outlook (Revenue, USD Billion; 2019 - 2030)

  • Cloud

  • On-premise

• Enterprise Size Outlook (Revenue, USD Billion; 2019 - 2030)

  • SMEs

  • Large Enterprise

• Automation Used Outlook (Revenue, USD Billion; 2019 - 2030)

  • Internet of Things (IoT)

  • Machine Learning (ML)

  • Others

• Industry Verticals Outlook (Revenue, USD Billion; 2019 - 2030)

  • Manufacturing

  • Retail & E-commerce

  • Logistics and Transportation

  • Healthcare

  • Food and Beverage

  • Others

• Regional Outlook (Revenue, USD Billion; 2019 - 2030)

  • North America 

    • U.S.

    • Canada

  • Europe

    • Germany

    • U.K.

    • France

  • Asia-Pacific

    • China

    • India

    • Japan

    • South Korea

    • Australia

  • Latin America

    • Brazil

    • Mexico

  • Middle East & Africa

    • KSA

    • UAE

    • South Korea