Artificial Intelligence in Retail Market to Surge from USD 8.24 Billion in 2023 to USD 36.87 Billion by 2030, Growing at a 23.87% CAGR 

Global Artificial Intelligence in Retail Market Expected to Reach USD 36.87 Billion by 2030, Growing at a CAGR of 23.87%

Summary:

The Global Artificial Intelligence (AI) in Retail Market was valued at USD 8.24 billion in 2023 and is projected to grow significantly, reaching nearly USD 36.87 billion by 2030. This growth is attributed to the increasing adoption of AI technologies by retailers to enhance customer experience and streamline operations.

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A) Market Size

The AI in Retail Market is poised for substantial growth, with a remarkable Compound Annual Growth Rate (CAGR) of 23.87% anticipated from 2024 to 2030. This surge reflects the industry's commitment to leveraging advanced technologies to meet evolving consumer demands.

B) Scope and Research Methodology

This comprehensive research report delves into the nuances of the AI in Retail market, analyzing key players, market segments, and the regulatory landscape. The study employs both qualitative and quantitative research methodologies, offering a well-rounded perspective on market dynamics.

C) Report Coverage

The report covers the latest trends and developments within the AI in Retail sector, including trade regulations, import/export analysis, and value chain optimization. Insights into economic and political factors affecting the market are also provided, equipping businesses with the knowledge necessary to navigate challenges and seize opportunities.

D) Overview

The Maximize Market Research report presents an overview of the Global AI in Retail market, emphasizing the importance of understanding local dynamics, including energy, economic, and political factors. This comprehensive approach enables businesses to craft effective strategies that align with market conditions.

E) Dynamics

The report identifies key drivers influencing market growth, such as the rise of e-commerce, the demand for personalized shopping experiences, and advancements in machine learning and natural language processing. However, it also highlights challenges, including data privacy concerns and the need for significant investments in technology.

F) Segmentation

The AI in Retail market is segmented by:

• Type: Online and Offline

• Solution: Product Recommendation & Planning, Customer Relationship Management, Visual Search, Virtual Assistant, Price Optimization, Payment Services Management, Supply Chain Management & Demand Planning, and Others.

• Technology: Machine Learning & Deep Learning, Natural Language Processing, and Others.

• Deployment Mode: Cloud and On-Premises.

• Application: Predictive Merchandising, Programmatic Advertising, Market Forecasting, In-Store Visual Monitoring and Surveillance, Location-Based Marketing, and Others.

G) Key Players Include

• IBM Corporation

• Microsoft Corporation

• Amazon Web Services

• Oracle

• SAP

• Google Inc.

• NVIDIA Corporation

• Intel Corporation

• Sentient Technologies

• Numenta Inc.

• Salesforce

• ViSenze

• Inbenta Technologies

• Interactions LLC

• Lexalytics Inc.

H) Key Offerings

The report offers valuable insights into market share, size, and forecasts by revenue from 2024 to 2030. It covers market dynamics, including growth drivers, restraints, and key trends, along with detailed market segmentation and competitive landscape analysis.

I) Table of Contents

1. Executive Summary

2. Introduction

3. Market Overview

4. Market Dynamics

   • Drivers

   • Restraints

5. Market Segmentation

   • By Type

   • By Solution

   • By Technology

   • By Deployment Mode

   • By Application

6. Regional Analysis

7. Competitive Landscape

8. Key Players

9. Conclusion

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About Us:

Maximize Market Research is a leading market research and business consulting firm dedicated to providing actionable insights and driving revenue growth for clients across various industries. With a strong focus on delivering comprehensive market analyses, we are committed to helping businesses navigate competitive environments effectively.

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