AX (AI Transformation) Strategies in Retail Businesses

Retailers

The retail industry is rapidly adopting artificial intelligence (AI)-powered business processes in the face of labor shortages, cost increases and diversified consumer needs. System vendors offer various AI use cases, including store operations and headquarters functions. Retailers have expanded their use of these applications to include customer service, sales promotions, sales floor management, inventory distribution, business strategies, and back-office work.
However, the actual implementation areas and the areas in which adoption has yielded results have not been visualized.  Additionally, there is a lack of visibility into the specific use cases being employed within particular retail sectors and across different operational domains.
This survey clarifies and quantitatively presents the implementation status, effects, and challenges of AI use cases by operational domain in the retail industry. The report aims to provide strategic data that contribute to sales strategies for vendors and system integrators. 

1. Executive Summary (Overview)

1-1. Background and Research Objectives of This Survey
1-2. Three Major Trends in AI Adoption in the Retail Industry
1-3. Current Status of AI Investment, Perceived Benefits, and Implementation Structures
1-4. Strategic Implications for Retail Companies and AI Vendors

2. Basic Attributes of Responding Companies (Profile)

2-1. Composition by Primary Industry Category (Profile 1)
2-2. Composition by Annual Sales Volume (Profile 2)
2-3. Sample Characteristics and Considerations for Analysis

3. Detailed Analysis by Question (Overall and by Industry)

3-1. Q1: Status of AI Adoption
3-2. Q2: Timing of AI Adoption (Scheduled Start Date)
3-3. Q3: AI Technologies Being Adopted or Considered
3-4. Q4: AI Software Being Adopted or Considered
3-5. Q5: Business Areas Where AI Is Being Utilized or Considered
3-6. Q6: Most Frequently Used AI Use Cases (Overall)
3-7. Q6-1: Top AI Use Case (First Place Only)
3-8. Q7: Purpose of AI Implementation
3-9. Q8: Areas Where AI Implementation Is Yielding Results
3-10. Q9: Challenges and Barriers to AI Implementation
3-11. Q10: ROI (Return on Investment) of AI Implementation
3-12. Q11 Business Areas Where AI Is Difficult to Utilize or Has Low Accuracy
3-13. Q12 Annual Investment in AI (Approximate)
3-14. Q13 AI Investment Strategy for the Next 1–2 Years
3-15. Q14 Planning, Development, and Operations Framework for AI Utilization
3-16. Q15 Key Considerations When Selecting AI Vendors and System Integrators

4. Analysis of Specific Use Cases and AI Products Used in Recruitment

4-1. Rankings and Characteristics of Recruitment Software and Tools (Q4FA)
4-2. Details on Specific Use Cases by Business Area (Q5-1)
4-3. In-Depth Analysis of Areas Where AI Adoption Is Progressing and Those Where It Is Not (Qualitative Comment Analysis)

5. In-Depth Cross-Tabulation Analysis (Challenges and Selection Criteria by Implementation Status)

5-1. Comparative Analysis of Challenges and Barriers by Implementation Status (Q9)
5-2. Comparison of Key Selection Criteria for AI Vendors and System Integrators by Implementation Status (Q15)
5-3. Stages of AI Adoption Maturity in the Retail Industry

6. AI Adoption Profiles by Major Industry (Profiles of 8 Industries)

6-1. Supermarkets
6-2. Drugstores
6-3. GMS (General Merchandise Stores)
6-4. Fashion Specialty Stores
6-5. Department Stores
6-6. DIY Stores and Electronics Retailers
6-7. E-commerce Operators
6-8. Other Retail Sectors
Appendix 1. Current Status of AI Adoption in Apparel Companies
Appendix 2. Status of AI Adoption in Overseas Retail Markets (U.S. and China)
Appendix 3. Case Studies of AI Adoption by Japanese Companies (by Business Area)