The AI store manager tool market size stands strong at US$ 74.4 million in 2024. The ongoing trend of smart tools is widening, and various industrial sectors are adopting AI-driven facilities. Therefore, the market is inclined to expand to US$ 160.5 million by 2034, covering a CAGR of 8.00% through 2034.
Factors Taking the AI Store Manager Tool Market Forward
AI-powered tools are emerging as top tools for retail stores, and the growth has been nascent; foreseeing the advancements in these tools, the market is predicted to flourish broadly. Some of the growth factors contributing to the interplay of advanced connectivity and retail sectors are mentioned below:
| Attributes | Key Statistics |
|---|---|
| Expected Base Year Value (2024) | US$ 74.4 million |
| Anticipated Forecast Value (2034) | US$ 160.5 million |
| Estimated Growth (2024 to 2034) | 8.00% CAGR |
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The future of the market is promising as modern stores and retailers are going to adopt such tools to streamline their daily operations. But this promise underlies certain challenges that could slow the market growth of smart tools.
Research conducted by Future Market Insights has analyzed data to harness the competition within the AI store manager tool market - the AI-enabled testing tool market and the automation testing market. Since AI store manager tools are still considered a niche, identifying growth factors and challenges in the other two markets will be beneficial to reach that stage.
AI Store Manager Tool Market:
| Attributes | AI Store Manager Tool Market |
|---|---|
| CAGR (2024 to 2034) | 8.00% |
| Market Value (2034) | US$ 160.5 million |
| Growth Factor | Demand for data-driven insights and analytics to enhance customer experience and drive sales |
| Key Challenges | Resistance to change and adoption barriers among traditional retailers due to unfamiliarity with AI technology |
AI-enabled Testing Tool Market:
| Attributes | AI-enabled Testing Tool Market |
|---|---|
| CAGR (2024 to 2034) | 16.90% |
| Market Value (2034) | US$ 2,373.95 million |
| Growth Factor | Integration of AI testing tools with DevOps pipelines and cloud-based testing environments |
| Key Challenges | Complexity in integrating AI testing tools with existing testing frameworks and environments |
Automation Testing Market:
| Attributes | Automation Testing Market |
|---|---|
| CAGR (2024 to 2034) | 14.30% |
| Market Value (2034) | US$ 122.82 billion |
| Growth Factor | Cost savings and productivity gains through reduced manual testing efforts and faster time-to-market |
| Key Challenges | Challenges in automating complex scenarios, UI testing, and end-to-end integration testing |
Principal Consultant
Inventory management system is the top application of AI store manager tools for the retail market, with a market share of 36.00% for 2024.
| Attributes | Details |
|---|---|
| Application | Inventory Management System |
| Market Share (2024) | 36.00% |
The ability of AI store manager tools to optimize stock levels, streamline supply chain operations, and provide real-time insights into product availability makes them an accessible choice in many sectors. In the retail market, efficient inventory management is crucial for minimizing stockouts, reducing excess inventory, and improving overall operational efficiency.
AI-powered inventory management tools have advanced features such as demand forecasting, automatic replenishment, and intelligent analysis, enabling retailers to make data-driven decisions. This also enhances customer satisfaction and ultimately improves their bottom line. This market-specific focus on inventory management reflects the growing demand for AI-driven solutions and can address the unique challenges of the retail industry, driving tangible business outcomes.
Medium-sized enterprises, with a market share of 35.00% for 2024, are experiencing growth in the AI store manager tool market.
| Attributes | Details |
|---|---|
| Enterprise Size | Medium-sized Enterprise (100-499 employees) |
| Market Share (2024) | 35.00% |
Medium-sized enterprises (100-499 employees) in the retail industry typically turn to AI store manager tools to manage their inventory efficiently. These tools are specifically designed to address the unique challenges faced by mid-sized retailers.
Balancing stock levels, optimizing supply chain operations, and gaining real-time insights into product availability are streamlined using AI-powered inventory management tools. Medium-sized enterprises can streamline their operations, improve customer satisfaction, and make data-driven decisions to enhance their overall business performance through AI store manager tools.
Countries like Australia and New Zealand, China, the United States, Germany, and Japan are expanding broadly in the AI store manager tool market.
| Countries | CAGR from 2024 to 2034 |
|---|---|
| Australia and New Zealand | 11.50% |
| China | 8.50% |
| United States | 4.90% |
| Japan | 1.80% |
| Germany | 1.50% |
Australia and New Zealand, with a remarkable CAGR of 11.50% for the forecast period, are experiencing broad growth in the automated retail management solutions market.
These regions face geographical challenges such as vast distances and dispersed populations, particularly in rural areas. AI store manager tools can help retailers overcome these challenges by optimizing inventory and facilitating logistics and distribution.
Companies can use these tools to enable online retailing and reach customers in remote locations, thus expanding their market reach. This is a key factor contributing to the ongoing growth of the retail sector in Australia and New Zealand through AI tools.
Australia has a significant portion of small to medium-sized retail enterprises, and smart store management tools allow these businesses to leverage advanced technology without requiring large-scale investment.
The retail sector in China is experiencing rapid growth influenced by urbanization, rising incomes, and increasing consumer demand. AI-driven retail operations help retailers capitalize on the market, improving overall operational efficiency. This ongoing growth in managing tools, with a CAGR of 8.50% through 2034, is leading the growth in the Chinese market.
Another wave of growth is the heavy contribution of the government actively supporting the development and adoption of AI technologies in the country. These initiatives pointed at driving economic growth and innovation in China are fueling market growth.
Funding for AI research and development, favorable regulatory policies, and initiatives to promote AI adoption across various industries have propelled China’s AI market, accelerating the adoption of these tools.
The United States has one of the most developed and competitive retail sectors globally. With the emerging rise of eCommerce giants like Amazon and the prevalence of brick-and-mortar stores, there's intense competition to optimize store operations. With a CAGR of 4.90%, the United States AI store manager tool market is gaining attention with rising demand in the market.
AI tools offer capabilities such as demand forecasting, inventory management, and personalized customer experiences. They provide the vitality needed to stay competitive in the market. With customization and premiumization of goods, the intelligent store management platforms market is thriving in various packaging sectors in the United States. This makes logistics and customer experience more satisfying, necessitating their presence.
Japan is one of the prominent players in the high-tech retail environment, with a strong emphasis on innovation and customer experience. Japan is anticipated to exhibit slow-paced growth in the AI store manager tool market with a CAGR of 1.80% through 2034 despite advancements.
Machine learning retail management software aligns with the trend of offering features like personalized product recommendations. AI-powered chatbots for customer support and real-time analytics to optimize store layouts and product placement are all features that contribute to the popularity of the AI smart tools market in Japan.
AI smart manager tools work efficiently on high-speed internet. Therefore, 5G is the desired network capability for these tools. About 70 million consumers in Japan have access to 5G, providing them with the platform to enable the usage of AI-driven tools.
Analyzing the artificial intelligence for the retail management industry in Germany, the AI-powered store management software market is set to grow with a steady flow. A CAGR of 1.50% from 2024 to 2034 shows a spurring adoption of AI tools in Germany.
Known for its strong manufacturing base, which extends to the retail and various industrial sectors, Germany is exploring trends in smart store management tools. Even though Germany-based businesses are significantly lagging in the global AI race, integrating these tools with existing manufacturing systems to optimize supply chain processes and improve overall operational efficiency can prove to be a boon for market growth in Germany.
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The AI store manager tool market is majorly controlled by a few powerful entities. However, as with any AI-related field, startups and new entrants threaten to disrupt the hold of these market giants.
Big brands are predicting shopper demands and enhancing user experiences. Developers are working on enabling features catering to the ongoing needs of retailers and all-sized enterprises, facilitating their operations in a more accessible way. Market players are facilitating enhanced shopping experiences, supporting store associates, and improving retail media campaigns to educate and expand the usage of these automated retail management solutions.
Recent Advancements
The market is set to reach US$ 74.4 million by 2024.
The AI store manager tool market is expected to reach US$ 160.5 million by 2034.
The market is growing at a CAGR of 8.00 % from 2024 to 2034.
Inventory management system is the top application, with a market share of 36.00% for 2024.
The market in China is expected to progress at a CAGR of 8.50% through 2034.
1. Executive Summary 1.1. Global Market Outlook 1.2. Demand-side Trends 1.3. Supply-side Trends 1.4. Technology Roadmap Analysis 1.5. Analysis and Recommendations 2. Market Overview 2.1. Market Coverage / Taxonomy 2.2. Market Definition / Scope / Limitations 3. Market Background 3.1. Market Dynamics 3.1.1. Drivers 3.1.2. Restraints 3.1.3. Opportunity 3.1.4. Trends 3.2. Scenario Forecast 3.2.1. Demand in Optimistic Scenario 3.2.2. Demand in Likely Scenario 3.2.3. Demand in Conservative Scenario 3.3. Opportunity Map Analysis 3.4. Investment Feasibility Matrix 3.5. PESTLE and Porter’s Analysis 3.6. Regulatory Landscape 3.6.1. By Key Regions 3.6.2. By Key Countries 3.7. Regional Parent Market Outlook 4. Global Market Analysis 2019 to 2023 and Forecast, 2024 to 2034 4.1. Historical Market Size Value (US$ Million) Analysis, 2019 to 2023 4.2. Current and Future Market Size Value (US$ Million) Projections, 2024 to 2034 4.2.1. Y-o-Y Growth Trend Analysis 4.2.2. Absolute $ Opportunity Analysis 5. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Solution 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Solution, 2019 to 2023 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Solution, 2024 to 2034 5.3.1. AI Store Manager Software 5.3.1.1. Cloud-Based 5.3.1.2. On-Premises 5.3.2. Services 5.3.2.1. Design & Implementation 5.3.2.2. Technology Consulting 5.3.2.3. Support Services 5.4. Y-o-Y Growth Trend Analysis By Solution, 2019 to 2023 5.5. Absolute $ Opportunity Analysis By Solution, 2024 to 2034 6. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Enterprise Size 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Enterprise Size, 2019 to 2023 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Enterprise Size, 2024 to 2034 6.3.1. SMEs 6.3.2. Large Enterprises 6.4. Y-o-Y Growth Trend Analysis By Enterprise Size, 2019 to 2023 6.5. Absolute $ Opportunity Analysis By Enterprise Size, 2024 to 2034 7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By End User 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By End User, 2019 to 2023 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By End User, 2024 to 2034 7.3.1. Supermarkets 7.3.2. Specialty Retail Stores 7.3.3. Grocery Stores 7.3.4. Retail Pharmacies 7.3.5. Others 7.4. Y-o-Y Growth Trend Analysis By End User, 2019 to 2023 7.5. Absolute $ Opportunity Analysis By End User, 2024 to 2034 8. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Region 8.1. Introduction 8.2. Historical Market Size Value (US$ Million) Analysis By Region, 2019 to 2023 8.3. Current Market Size Value (US$ Million) Analysis and Forecast By Region, 2024 to 2034 8.3.1. North America 8.3.2. Latin America 8.3.3. Western Europe 8.3.4. Eastern Europe 8.3.5. South Asia and Pacific 8.3.6. East Asia 8.3.7. Middle East and Africa 8.4. Market Attractiveness Analysis By Region 9. North America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 9.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 9.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 9.2.1. By Country 9.2.1.1. USA 9.2.1.2. Canada 9.2.2. By Solution 9.2.3. By Enterprise Size 9.2.4. By End User 9.3. Market Attractiveness Analysis 9.3.1. By Country 9.3.2. By Solution 9.3.3. By Enterprise Size 9.3.4. By End User 9.4. Key Takeaways 10. Latin America Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 10.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 10.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 10.2.1. By Country 10.2.1.1. Brazil 10.2.1.2. Mexico 10.2.1.3. Rest of Latin America 10.2.2. By Solution 10.2.3. By Enterprise Size 10.2.4. By End User 10.3. Market Attractiveness Analysis 10.3.1. By Country 10.3.2. By Solution 10.3.3. By Enterprise Size 10.3.4. By End User 10.4. Key Takeaways 11. Western Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 11.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 11.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 11.2.1. By Country 11.2.1.1. Germany 11.2.1.2. UK 11.2.1.3. France 11.2.1.4. Spain 11.2.1.5. Italy 11.2.1.6. Rest of Western Europe 11.2.2. By Solution 11.2.3. By Enterprise Size 11.2.4. By End User 11.3. Market Attractiveness Analysis 11.3.1. By Country 11.3.2. By Solution 11.3.3. By Enterprise Size 11.3.4. By End User 11.4. Key Takeaways 12. Eastern Europe Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 12.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 12.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 12.2.1. By Country 12.2.1.1. Poland 12.2.1.2. Russia 12.2.1.3. Czech Republic 12.2.1.4. Romania 12.2.1.5. Rest of Eastern Europe 12.2.2. By Solution 12.2.3. By Enterprise Size 12.2.4. By End User 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Solution 12.3.3. By Enterprise Size 12.3.4. By End User 12.4. Key Takeaways 13. South Asia and Pacific Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 13.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 13.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 13.2.1. By Country 13.2.1.1. India 13.2.1.2. Bangladesh 13.2.1.3. Australia 13.2.1.4. New Zealand 13.2.1.5. Rest of South Asia and Pacific 13.2.2. By Solution 13.2.3. By Enterprise Size 13.2.4. By End User 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Solution 13.3.3. By Enterprise Size 13.3.4. By End User 13.4. Key Takeaways 14. East Asia Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 14.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 14.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 14.2.1. By Country 14.2.1.1. China 14.2.1.2. Japan 14.2.1.3. South Korea 14.2.2. By Solution 14.2.3. By Enterprise Size 14.2.4. By End User 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Solution 14.3.3. By Enterprise Size 14.3.4. By End User 14.4. Key Takeaways 15. Middle East and Africa Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Country 15.1. Historical Market Size Value (US$ Million) Trend Analysis By Market Taxonomy, 2019 to 2023 15.2. Market Size Value (US$ Million) Forecast By Market Taxonomy, 2024 to 2034 15.2.1. By Country 15.2.1.1. GCC Countries 15.2.1.2. South Africa 15.2.1.3. Israel 15.2.1.4. Rest of MEA 15.2.2. By Solution 15.2.3. By Enterprise Size 15.2.4. By End User 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Solution 15.3.3. By Enterprise Size 15.3.4. By End User 15.4. Key Takeaways 16. Key Countries Market Analysis 16.1. USA 16.1.1. Market Share Analysis, 2023 16.1.1.1. By Solution 16.1.1.2. By Enterprise Size 16.1.1.3. By End User 16.2. Canada 16.2.1. Market Share Analysis, 2023 16.2.1.1. By Solution 16.2.1.2. By Enterprise Size 16.2.1.3. By End User 16.3. Brazil 16.3.1. Market Share Analysis, 2023 16.3.1.1. By Solution 16.3.1.2. By Enterprise Size 16.3.1.3. By End User 16.4. Mexico 16.4.1. Market Share Analysis, 2023 16.4.1.1. By Solution 16.4.1.2. By Enterprise Size 16.4.1.3. By End User 16.5. Germany 16.5.1. Market Share Analysis, 2023 16.5.1.1. By Solution 16.5.1.2. By Enterprise Size 16.5.1.3. By End User 16.6. UK 16.6.1. Market Share Analysis, 2023 16.6.1.1. By Solution 16.6.1.2. By Enterprise Size 16.6.1.3. By End User 16.7. France 16.7.1. Market Share Analysis, 2023 16.7.1.1. By Solution 16.7.1.2. By Enterprise Size 16.7.1.3. By End User 16.8. Spain 16.8.1. Market Share Analysis, 2023 16.8.1.1. By Solution 16.8.1.2. By Enterprise Size 16.8.1.3. By End User 16.9. Italy 16.9.1. Market Share Analysis, 2023 16.9.1.1. By Solution 16.9.1.2. By Enterprise Size 16.9.1.3. By End User 16.10. Poland 16.10.1. Market Share Analysis, 2023 16.10.1.1. By Solution 16.10.1.2. By Enterprise Size 16.10.1.3. By End User 16.11. Russia 16.11.1. Market Share Analysis, 2023 16.11.1.1. By Solution 16.11.1.2. By Enterprise Size 16.11.1.3. By End User 16.12. Czech Republic 16.12.1. Market Share Analysis, 2023 16.12.1.1. By Solution 16.12.1.2. By Enterprise Size 16.12.1.3. By End User 16.13. Romania 16.13.1. Market Share Analysis, 2023 16.13.1.1. By Solution 16.13.1.2. By Enterprise Size 16.13.1.3. By End User 16.14. India 16.14.1. Market Share Analysis, 2023 16.14.1.1. By Solution 16.14.1.2. By Enterprise Size 16.14.1.3. By End User 16.15. Bangladesh 16.15.1. Market Share Analysis, 2023 16.15.1.1. By Solution 16.15.1.2. By Enterprise Size 16.15.1.3. By End User 16.16. Australia 16.16.1. Market Share Analysis, 2023 16.16.1.1. By Solution 16.16.1.2. By Enterprise Size 16.16.1.3. By End User 16.17. New Zealand 16.17.1. Market Share Analysis, 2023 16.17.1.1. By Solution 16.17.1.2. By Enterprise Size 16.17.1.3. By End User 16.18. China 16.18.1. Market Share Analysis, 2023 16.18.1.1. By Solution 16.18.1.2. By Enterprise Size 16.18.1.3. By End User 16.19. Japan 16.19.1. Market Share Analysis, 2023 16.19.1.1. By Solution 16.19.1.2. By Enterprise Size 16.19.1.3. By End User 16.20. South Korea 16.20.1. Market Share Analysis, 2023 16.20.1.1. By Solution 16.20.1.2. By Enterprise Size 16.20.1.3. By End User 16.21. GCC Countries 16.21.1. Market Share Analysis, 2023 16.21.1.1. By Solution 16.21.1.2. By Enterprise Size 16.21.1.3. By End User 16.22. South Africa 16.22.1. Market Share Analysis, 2023 16.22.1.1. By Solution 16.22.1.2. By Enterprise Size 16.22.1.3. By End User 16.23. Israel 16.23.1. Market Share Analysis, 2023 16.23.1.1. By Solution 16.23.1.2. By Enterprise Size 16.23.1.3. By End User 17. Market Structure Analysis 17.1. Competition Dashboard 17.2. Competition Benchmarking 17.3. Market Share Analysis of Top Players 17.3.1. By Regional 17.3.2. By Solution 17.3.3. By Enterprise Size 17.3.4. By End User 18. Competition Analysis 18.1. Competition Deep Dive 18.1.1. Deepgram 18.1.1.1. Overview 18.1.1.2. Product Portfolio 18.1.1.3. Profitability by Market Segments 18.1.1.4. Sales Footprint 18.1.1.5. Strategy Overview 18.1.1.5.1. Marketing Strategy 18.1.2. Visive.ai 18.1.2.1. Overview 18.1.2.2. Product Portfolio 18.1.2.3. Profitability by Market Segments 18.1.2.4. Sales Footprint 18.1.2.5. Strategy Overview 18.1.2.5.1. Marketing Strategy 18.1.3. Retalon 18.1.3.1. Overview 18.1.3.2. Product Portfolio 18.1.3.3. Profitability by Market Segments 18.1.3.4. Sales Footprint 18.1.3.5. Strategy Overview 18.1.3.5.1. Marketing Strategy 18.1.4. HoneyDo 18.1.4.1. Overview 18.1.4.2. Product Portfolio 18.1.4.3. Profitability by Market Segments 18.1.4.4. Sales Footprint 18.1.4.5. Strategy Overview 18.1.4.5.1. Marketing Strategy 18.1.5. Quinyx 18.1.5.1. Overview 18.1.5.2. Product Portfolio 18.1.5.3. Profitability by Market Segments 18.1.5.4. Sales Footprint 18.1.5.5. Strategy Overview 18.1.5.5.1. Marketing Strategy 18.1.6. Product Hunt 18.1.6.1. Overview 18.1.6.2. Product Portfolio 18.1.6.3. Profitability by Market Segments 18.1.6.4. Sales Footprint 18.1.6.5. Strategy Overview 18.1.6.5.1. Marketing Strategy 18.1.7. Stork AI 18.1.7.1. Overview 18.1.7.2. Product Portfolio 18.1.7.3. Profitability by Market Segments 18.1.7.4. Sales Footprint 18.1.7.5. Strategy Overview 18.1.7.5.1. Marketing Strategy 18.1.8. Welcome AI 18.1.8.1. Overview 18.1.8.2. Product Portfolio 18.1.8.3. Profitability by Market Segments 18.1.8.4. Sales Footprint 18.1.8.5. Strategy Overview 18.1.8.5.1. Marketing Strategy 18.1.9. ShopMate 18.1.9.1. Overview 18.1.9.2. Product Portfolio 18.1.9.3. Profitability by Market Segments 18.1.9.4. Sales Footprint 18.1.9.5. Strategy Overview 18.1.9.5.1. Marketing Strategy 19. Assumptions & Acronyms Used 20. Research Methodology
Technology
July 2017
REP-GB-4308
August 2022
342 pages
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AI Store Manager Tool Market
