Generative AI In Supply Chain Market Size, Share, and Trends 2026 to 2035

Generative AI In Supply Chain Market (By Deployment Mode: Cloud-based, On-Premise; By End-User: Retail, Healthcare, Manufacturing) - Global Industry Analysis, Size, Trends, Leading Companies, Regional Outlook, and Forecast 2026 to 2035

Last Updated : 05 Jan 2026  |  Report Code : 3124  |  Category : ICT   |  Format : PDF / PPT / Excel

Chapter 1. Introduction

1.1. Research Objective

1.2. Scope of the Study

1.3. Definition

Chapter 2. Research Methodology 

2.1. Research Approach

2.2. Data Sources

2.3. Assumptions & Limitations

Chapter 3. Executive Summary

3.1. Market Snapshot

Chapter 4. Market Variables and Scope 

4.1. Introduction

4.2. Market Classification and Scope

4.3. Industry Value Chain Analysis

4.3.1. Raw Material Procurement Analysis 

4.3.2. Sales and Distribution Channel Analysis

4.3.3. Downstream Buyer Analysis

Chapter 5. COVID 19 Impact on Generative AI in Supply Chain Market 

5.1. COVID-19 Landscape: Generative AI in Supply Chain Industry Impact

5.2. COVID 19 - Impact Assessment for the Industry

5.3. COVID 19 Impact: Global Major Government Policy

5.4. Market Trends and Opportunities in the COVID-19 Landscape

6.1. Market Dynamics

6.1.1. Market Drivers

6.1.2. Market Restraints

6.1.3. Market Opportunities

6.2. Porter’s Five Forces Analysis

6.2.1. Bargaining power of suppliers

6.2.2. Bargaining power of buyers

6.2.3. Threat of substitute

6.2.4. Threat of new entrants

6.2.5. Degree of competition

Chapter 7. Competitive Landscape

7.1.1. Company Market Share/Positioning Analysis

7.1.2. Key Strategies Adopted by Players

7.1.3. Vendor Landscape

7.1.3.1. List of Suppliers

7.1.3.2. List of Buyers

Chapter 8. Global Generative AI in Supply Chain Market, By Deployment Mode

8.1. Generative AI in Supply Chain Market, by Deployment Mode

8.1.1. Cloud-based

8.1.1.1. Market Revenue and Forecast

8.1.2. On-Premise

8.1.2.1. Market Revenue and Forecast

Chapter 9. Global Generative AI in Supply Chain Market, By End-User

9.1. Generative AI in Supply Chain Market, by End-User

9.1.1. Retail

9.1.1.1. Market Revenue and Forecast

9.1.2. Healthcare

9.1.2.1. Market Revenue and Forecast

9.1.3. Manufacturing

9.1.3.1. Market Revenue and Forecast

Chapter 10. Global Generative AI in Supply Chain Market, Regional Estimates and Trend Forecast

10.1. North America

10.1.1. Market Revenue and Forecast, by Deployment Mode

10.1.2. Market Revenue and Forecast, by End-User

10.1.3. U.S.

10.1.3.1. Market Revenue and Forecast, by Deployment Mode

10.1.3.2. Market Revenue and Forecast, by End-User

10.1.4. Rest of North America

10.1.4.1. Market Revenue and Forecast, by Deployment Mode

10.1.4.2. Market Revenue and Forecast, by End-User

10.2. Europe

10.2.1. Market Revenue and Forecast, by Deployment Mode

10.2.2. Market Revenue and Forecast, by End-User

10.2.3. UK

10.2.3.1. Market Revenue and Forecast, by Deployment Mode

10.2.3.2. Market Revenue and Forecast, by End-User

10.2.4. Germany

10.2.4.1. Market Revenue and Forecast, by Deployment Mode

10.2.4.2. Market Revenue and Forecast, by End-User

10.2.5. France

10.2.5.1. Market Revenue and Forecast, by Deployment Mode

10.2.5.2. Market Revenue and Forecast, by End-User

10.2.6. Rest of Europe

10.2.6.1. Market Revenue and Forecast, by Deployment Mode

10.2.6.2. Market Revenue and Forecast, by End-User

10.3. APAC

10.3.1. Market Revenue and Forecast, by Deployment Mode

10.3.2. Market Revenue and Forecast, by End-User

10.3.3. India

10.3.3.1. Market Revenue and Forecast, by Deployment Mode

10.3.3.2. Market Revenue and Forecast, by End-User

10.3.4. China

10.3.4.1. Market Revenue and Forecast, by Deployment Mode

10.3.4.2. Market Revenue and Forecast, by End-User

10.3.5. Japan

10.3.5.1. Market Revenue and Forecast, by Deployment Mode

10.3.5.2. Market Revenue and Forecast, by End-User

10.3.6. Rest of APAC

10.3.6.1. Market Revenue and Forecast, by Deployment Mode

10.3.6.2. Market Revenue and Forecast, by End-User

10.4. MEA

10.4.1. Market Revenue and Forecast, by Deployment Mode

10.4.2. Market Revenue and Forecast, by End-User

10.4.3. GCC

10.4.3.1. Market Revenue and Forecast, by Deployment Mode

10.4.3.2. Market Revenue and Forecast, by End-User

10.4.4. North Africa

10.4.4.1. Market Revenue and Forecast, by Deployment Mode

10.4.4.2. Market Revenue and Forecast, by End-User

10.4.5. South Africa

10.4.5.1. Market Revenue and Forecast, by Deployment Mode

10.4.5.2. Market Revenue and Forecast, by End-User

10.4.6. Rest of MEA

10.4.6.1. Market Revenue and Forecast, by Deployment Mode

10.4.6.2. Market Revenue and Forecast, by End-User

10.5. Latin America

10.5.1. Market Revenue and Forecast, by Deployment Mode

10.5.2. Market Revenue and Forecast, by End-User

10.5.3. Brazil

10.5.3.1. Market Revenue and Forecast, by Deployment Mode

10.5.3.2. Market Revenue and Forecast, by End-User

10.5.4. Rest of LATAM

10.5.4.1. Market Revenue and Forecast, by Deployment Mode

10.5.4.2. Market Revenue and Forecast, by End-User

Chapter 11. Company Profiles

11.1. IBM Corporation

11.1.1. Company Overview

11.1.2. Product Offerings

11.1.3. Financial Performance

11.1.4. Recent Initiatives

11.2. Microsoft Corporation

11.2.1. Company Overview

11.2.2. Product Offerings

11.2.3. Financial Performance

11.2.4. Recent Initiatives

11.3. SAP SE

11.3.1. Company Overview

11.3.2. Product Offerings

11.3.3. Financial Performance

11.3.4. Recent Initiatives

11.4. Oracle Corporation

11.4.1. Company Overview

11.4.2. Product Offerings

11.4.3. Financial Performance

11.4.4. Recent Initiatives

11.5. Blue Yonder

11.5.1. Company Overview

11.5.2. Product Offerings

11.5.3. Financial Performance

11.5.4. Recent Initiatives

11.6. LLamasoft Inc

11.6.1. Company Overview

11.6.2. Product Offerings

11.6.3. Financial Performance

11.6.4. Recent Initiatives

11.7. AIMMS

11.7.1. Company Overview

11.7.2. Product Offerings

11.7.3. Financial Performance

11.7.4. Recent Initiatives

Chapter 12. Research Methodology

12.1. Primary Research

12.2. Secondary Research

12.3. Assumptions

Chapter 13. Appendix

13.1. About Us

13.2. Glossary of Terms

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Frequently Asked Questions

Answer : The global generative AI in supply chain market size is expected to increase USD 34,243.44 million by 2035 from USD 932.02 million in 2025.

Answer : The global generative AI in supply chain market will register growth rate of 43.39% between 2026 to 2035

Answer : The major players operating in the generative AI in supply chain market are IBM Corporation, Microsoft Corporation, SAP SE, Oracle Corporation, Blue Yonder, LLamasoft Inc, AIMMS, and Others.

Answer : The driving factors of the generative AI in supply chain market are the demand for efficient and cost-effective advanced solutions and minimization of the overall operational cost offered by generative AI.

Answer : North America region will lead the global generative AI in supply chain market during the forecast period 2026 to 2035

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