The AI in supply chain market is projected to grow from USD 9.15 billion in 2024 and is expected to reach USD 40.53 billion by 2030, growing at a CAGR of 28.2% from 2024 to 2030. AI has improved customers satisfaction toward consumer products. This improvement benefits the organization by maintaining sales tracking and hence garnering more customers. The machine learning techniques that involve deep analytics and real-time monitoring significantly enhance the supply chain visibility of the businesses and hence enable them to deliver better customer experiences and maintain the pace within the delivery timelines. Therefore, market players are employing AI-based supply chain management solutions to increase efficiency and productivity.
Scope of the Report
Years Considered for the Study
2020-2030
Base Year
2023
Forecast Period
2024-2030
Units Considered
Value (USD Billion)
Segments
By Application, Services, Software and Region
Regions covered
North America, Europe, APAC, RoW
"The cloud segment in the AI in supply chain market to witness higher growth rate during the forecast period."
Cloud segment is mainly driven by cloud-based solutions that are increasingly being adopted by small and medium enterprises, primarily because they provide the flexibility, scalability, and cost-effectiveness features that the organizations require. In addition, the speed in developing sophisticated security solutions for cloud-based deployment offers answers to issues that existed on data privacy and thus attract businesses seeking to adopt AI without investing in big premises-based infrastructure.
"The US is expected to hold the largest market size in the North America region during the forecast period."
The US companies face pressure and competition to reduce costs while maintaining high levels of customer service. AI supply chain solutions allow for the automation of tasks, analyzing big data, and generating actionable insights that might make efficiency, transparency, and agility inside the supply chain more efficient. There has been a manufacturing and logistics labor shortfall in the US. The use of AI helps to eliminate a human workforce so that activities relate more to higher-value tasks requiring expertise and experience. Further, the US is a leading country in AI research and development. This encourages the development of advanced AI solutions specifically for supply chain applications.
By Company Type: Tier 1 - 20%, Tier 2 - 35%, and Tier 3 - 45%
By Designation: C-level Executives - 15%, Directors -20%, and Others - 65%
By Region: North America -20%, Europe - 15%, Asia Pacific- 60%, and RoW - 5%
Players profiled in this report are SAP SE (Germany), Oracle (US), Blue Yonder Group, Inc. (US), Kinaxis Inc. (Canada), Manhattan Associates (US), NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Micron Technology, Inc. (US), Qualcomm Technologies, Inc. (US), SAMSUNG (South Korea), IBM (US), Microsoft (US), Amazon Web Services, Inc. (US), Google (US), Anaplan, Inc. (US), Logility Supply Chain Solutions, Inc. (US), Coupa (US), O9 Solutions, Inc. (US), Alibaba Group Holding Limited (China), FedEx Corporation (US), Deutsche Post AG (Germany), ServiceNow (US), Project44 (US), Resilinc Corporation (US), FourKites, Inc. (US), RELEX Solutions (Finland), C.H. Robinson Worldwide, Inc. (US), e2open, LLC (US), FERO.Ai (UAE) among a few other key companies in the AI in supply chain ecosystem.
Report Coverage
The report defines, describes, and forecasts the AI in supply chain market based on offering, deployment, organization size, application, end-use industry, and region. It provides detailed information regarding drivers, restraints, opportunities, and challenges influencing the growth of the AI in supply chain market. It also analyzes competitive developments such as acquisitions, product launches, expansions, and actions carried out by the key players to grow in the market.
Reasons to Buy This Report
The report will help the market leaders/new entrants in the market with information on the closest approximations of the revenue for the overall AI in supply chain market and the subsegments. The report will help stakeholders understand the competitive landscape and gain more insight to position their business better and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with information on key drivers, restraints, opportunities, and challenges.
The report will provide insights into the following pointers:
Analysis of key drivers (Big data enhance supply chain efficiency through data-driven decision making) restraints (Shortage of skilled workforce)
opportunities (Surge in increasing demand for intelligent business processes and automation), and challenges (Difficulties in data integration from multiple sources) of the AI in supply chain market.
Product development /Innovation: Detailed insights on upcoming technologies, research & development activities, and new product launches in the AI in supply chain market.
Market Development: Comprehensive information about lucrative markets; the report analyses the AI in supply chain market across various regions.
Market Diversification: Exhaustive information about new products launched, untapped geographies, recent developments, and investments in the AI in supply chain market.
Competitive Assessment: In-depth assessment of market share, growth strategies, and offering of leading players like SAP SE (Germany), Oracle (US), Blue Yonder Group, Inc. (US), Kinaxis Inc. (Canada), Manhattan Associates (US) among others in the AI in supply chain market.
TABLE OF CONTENTS
1 INTRODUCTION
1.1 STUDY OBJECTIVES
1.2 MARKET DEFINITION
1.3 STUDY SCOPE
1.3.1 MARKET SEGMENTATION
1.3.2 INCLUSIONS AND EXCLUSIONS
1.4 YEARS CONSIDERED
1.5 CURRENCY CONSIDERED
1.6 UNITS CONSIDERED
1.7 STAKEHOLDERS
1.8 SUMMARY OF CHANGES
2 RESEARCH METHODOLOGY
2.1 RESEARCH DATA
2.1.1 SECONDARY DATA
2.1.1.1 List of secondary sources
2.1.1.2 Key data from secondary sources
2.1.2 PRIMARY DATA
2.1.2.1 List of interview participants
2.1.2.2 Breakdown of primary interviews
2.1.2.3 Key data from primary sources
2.1.2.4 Insights from industry experts
2.1.3 SECONDARY AND PRIMARY RESEARCH
2.2 MARKET SIZE ESTIMATION
2.2.1 BOTTOM-UP APPROACH
2.2.1.1 Approach to estimate market size using bottom-up analysis (supply side)
2.2.2 TOP-DOWN APPROACH
2.2.2.1 Approach to estimate market size using top-down analysis (demand side)
2.3 DATA TRIANGULATION
2.4 RESEARCH ASSUMPTIONS
2.5 RESEARCH LIMITATIONS
2.6 RISK ASSESSMENT
3 EXECUTIVE SUMMARY
4 PREMIUM INSIGHTS
4.1 ATTRACTIVE OPPORTUNITIES FOR PLAYERS IN AI IN SUPPLY CHAIN MARKET
4.2 AI IN SUPPLY CHAIN MARKET, BY OFFERING
4.3 AI IN SUPPLY CHAIN MARKET, BY DEPLOYMENT
4.4 AI IN SUPPLY CHAIN MARKET, BY ORGANIZATION SIZE
4.5 NORTH AMERICA: AI IN SUPPLY CHAIN MARKET, BY DEPLOYMENT AND COUNTRY
4.6 GLOBAL AI IN SUPPLY CHAIN MARKET, BY COUNTRY
5 MARKET OVERVIEW
5.1 INTRODUCTION
5.2 MARKET DYNAMICS
5.2.1 DRIVERS
5.2.1.1 Growing implementation of big data and AI technologies
5.2.1.2 Need for enhanced visibility in supply chain processes
5.2.1.3 Rapid AI integration to improve customer satisfaction