The AI asset management tool market is set to progress at a CAGR of 10.60% through 2034. The market value is slated to increase from US$ 8,296.10 million in 2024 to US$ 3,029.16 million by 2034.
Attributes | Details |
---|---|
AI Asset Management Tool Market Size, 2024 | US$ 3,029.16 million |
AI Asset Management Tool Market Size, 2034 | US$ 8,296.10 million |
Value CAGR (2024 to 2034) | 10.60% |
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Keeping budgets in check fuels the adoption of AI asset management tools in the finance sector. The affluence of private banks sees them using AI asset management tools without much hesitation. Other factors influencing the market expansion include:
The sudden surge in technological advances in the business sector worldwide is impacting market growth. With developments in advanced technology, the sector is experiencing a revolution in its core assets such as asset management and others.
Several industries are seeking out the management of their important applications, such as trading, portfolio management, and risk management. As a result, AI has entered as an emerging aspect of this industry. Implementing the Internet of Things in industries also contributes to market growth.
The fintech sector has seen the need for advice in recent years. AI is creating significant opportunities in this sector. Robo-advising is gaining much popularity in the industry, particularly in fields such as democratizing investment advisory and robo-advisory, making it cheaper and more accessible to unsophisticated individual investors.
Manufacturers are continuously focusing on improving their tools. Emerging trends of AI are contributing to the growth of the industry, with a special focus on innovation and other streams. Moreover, the need to monitor asset performance is gaining attention toward tools that handle it swiftly and improve overall system reliability. Thus, AI asset management tools are gaining traction in the current period.
With the demand for improving efficacy in work related to data entry, compliance monitoring, and report generation, AI tools are increasingly used in this field. In the integration of AI in the asset management industry, several financial professionals and asset managers are adopting AI tools for their practices.
Improving risk management and fraud detection is on the rise. AI tools are significantly helping in the detection of market disruption, irregular trading patterns, and spotting unusual activities in fraud detection. These characteristics make AI tools a perfect and precise asset for several business activities.
All over the world, artificial intelligence is still developing and learning. It greatly depends on and can only work with subjects that it has already learned. The development of AI in states is anticipated to create lucrative opportunities in the coming years.
Generic response is another concern that acts as a headache for software manufacturers. AI can record and react to generic subjects common to all experiences, businesses, and others. Thus, businesses are seeking out tools that reduce the time for training and other facilities.
Need for data safety is the primary aim of all businesses across the world in the current period. Data safety is increasingly important, and all AI systems run on data. Organizations are developing secure systems to protect their data from cyber-attacks and digital theft.
Apart from the AI asset management tool market, an in-depth analysis has been done on two other related markets. These markets are the enterprise asset management market and the asset financing platform market.
Growing deployment of the Internet of Things in industries and the emergence of AI across the world are amplifying the adoption of enterprise asset management tools. Flexible financial solutions and the rise of eCommerce are expected to drive demand for asset financing platforms.
AI Asset Management Tool Market:
Attributes | AI Asset Management Tool Market |
---|---|
Value-based CAGR (2024 to 2034) | 10.60% |
Market Trend | Integration of machine learning algorithms for predictive asset maintenance |
Growth Opportunity | Development of AI tools for alternative asset classes like cryptocurrencies and NFTs |
Enterprise Asset Management Market:
Attributes | Enterprise Asset Management Market |
---|---|
Value-based CAGR (2024 to 2034) | 7% |
Market Trend | Shift toward mobile EAM applications for enhanced field workforce productivity |
Growth Opportunity | Implementation of blockchain technology for transparent asset tracking and management |
Asset Financing Platform Market:
Attributes | Asset Financing Platform Market |
---|---|
Value-based CAGR (2024 to 2034) | 9.3% |
Market Trend | Expansion of peer-to-peer (P2P) lending platforms for alternative asset financing options |
Growth Opportunity | Integration of Internet of Things (IoT) data for real-time asset performance monitoring and valuation |
Attributes | Details |
---|---|
Solution | Enterprise Asset Management (EAM) Systems |
Market share in 2024 | 28% |
The emergence of the Internet of Things deployment in industries to manage assets is a growing trend. To improve the efficacy and productivity of employees, AI integration is becoming increasingly popular in enterprise asset management systems. The escalating need for EAM solutions is likely to continue growing as more businesses invest in their IT infrastructure instead of investing in manual or physical infrastructure.
Attributes | Details |
---|---|
End User | Banks |
Market share in 2024 | 38.22% |
The need to analyze vast amounts of data and create personalized investment strategies is expected to drive the demand for AI asset management in banks. Banks are increasingly implementing AI in their processes to improve their work efficiency and financial clarity. Having a vast customer base and strategic relationships with clients gives the market an advantage.
For the management of rules and regulations, banks have effectively started using AI management tools. AI tools are helping them reduce errors and mitigate risks by providing a reliable and secure investment platform.
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Countries | Forecasted CAGR from 2024 to 2034 |
---|---|
United States | 7.50% |
Germany | 4.10% |
China | 11.10% |
Japan | 3.40% |
Australia | 14.10% |
New innovations and technologies are contributing to market growth in the United States. Several financial sectors are integrating them into their work or business for the security and clarity of financial assets. The United States is considered a technologically advanced region. Manufacturers in the United States are investing in research and development activities to upgrade their AI tools.
According to our analysis, 73% of companies in the United States are using AI in some aspect of their work or business. The banking sector of the United States is unpredictable and changing, and it is expected to create lucrative opportunities in the market. Latest AI related developments, such as Chatbots and conversational interfaces, are in high demand in the United States. Banks are relying on them to improve consumer experience and other facilities in the country.
China is a hub for technological advances. Financial institutions in China are increasingly restructuring their data management methods and strategies with the integration of AI. The artificial intelligence industry in China is rapidly evolving.
Government initiatives toward technology development are expected to drive the demand for the market in China. Governments are setting rules and regulations for companies operating in China, such as requiring each company to implement the development of a specialized AI sector in the country and others. Moreover, investors are looking for investment opportunities in China where the use of AI is prevalent.
The government in Germany is promoting the adoption of AI in the banking and other financial sectors in various ways. Other fintech companies are testing their innovative products and services in the current period.
With a vibrant fintech ecosystem and the rise of many startups using artificial intelligence to replace the traditional financial sector in Germany, several collaborations and partnerships have been observed between industries and institutes in Germany.
Financial institutes of Japan are looking to increase work efficiency and maintain market reputation. Japan is one step ahead of other regions in innovation and technology utilization. Some of the prominent factors driving the market include portfolio management, risk assessment, and others.
Australia is facing problems in the financial sector, such as complexity in financial products and services. As AI helps to monitor and analyze big data, asset managers are increasingly preferring AI asset management tools for their business.
The market is witnessing rapid development and evolution. Key players are investing in improving their tools to gain traction in the market. Several strategies are changing the market landscape by disrupting traditional asset management methods and introducing unique approaches.
The market is anticipated to experience exponential growth during the forecast period owing to research and innovations by market players. Many financial sectors are adopting AI asset management tools to improve their work efficacy and accuracy. Manufacturers are looking to boost customer loyalty by implementing new marketing strategies.
Recent Developments
The CAGR of the AI asset management tool market in the United States from 2024 to 2034 is estimated to be 7.50%.
The AI asset management tool market is expected to develop at a CAGR of 10.60% from 2024 to 2034.
The AI asset management tool market size is expected to be worth US$ 3,029.16 million in 2024.
The CAGR of the AI asset management tool market between 2024 and 2034 in China is estimated to be 11.10%.
The AI asset management tool market is estimated to get as big as US$ 8,296.10 million by 2034.
The AI asset management tool market can be segmented by solution, end user, and region.
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 Technology 5.1. Introduction / Key Findings 5.2. Historical Market Size Value (US$ Million) Analysis By Technology, 2019 to 2023 5.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Technology, 2024 to 2034 5.3.1. Machine Learning 5.3.2. Natural Language Processing (NLP) 5.3.3. Others 5.4. Y-o-Y Growth Trend Analysis By Technology, 2019 to 2023 5.5. Absolute $ Opportunity Analysis By Technology, 2024 to 2034 6. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Deployment Mode 6.1. Introduction / Key Findings 6.2. Historical Market Size Value (US$ Million) Analysis By Deployment Mode, 2019 to 2023 6.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Deployment Mode, 2024 to 2034 6.3.1. On-Premises 6.3.2. Cloud 6.4. Y-o-Y Growth Trend Analysis By Deployment Mode, 2019 to 2023 6.5. Absolute $ Opportunity Analysis By Deployment Mode, 2024 to 2034 7. Global Market Analysis 2019 to 2023 and Forecast 2024 to 2034, By Application 7.1. Introduction / Key Findings 7.2. Historical Market Size Value (US$ Million) Analysis By Application, 2019 to 2023 7.3. Current and Future Market Size Value (US$ Million) Analysis and Forecast By Application, 2024 to 2034 7.3.1. Portfolio Optimization 7.3.2. Conversational Platform 7.3.3. Risk & Compliance 7.3.4. Data Analysis 7.3.5. Process Automation 7.3.6. Others 7.4. Y-o-Y Growth Trend Analysis By Application, 2019 to 2023 7.5. Absolute $ Opportunity Analysis By Application, 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 Technology 9.2.3. By Deployment Mode 9.2.4. By Application 9.3. Market Attractiveness Analysis 9.3.1. By Country 9.3.2. By Technology 9.3.3. By Deployment Mode 9.3.4. By Application 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 Technology 10.2.3. By Deployment Mode 10.2.4. By Application 10.3. Market Attractiveness Analysis 10.3.1. By Country 10.3.2. By Technology 10.3.3. By Deployment Mode 10.3.4. By Application 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 Technology 11.2.3. By Deployment Mode 11.2.4. By Application 11.3. Market Attractiveness Analysis 11.3.1. By Country 11.3.2. By Technology 11.3.3. By Deployment Mode 11.3.4. By Application 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 Technology 12.2.3. By Deployment Mode 12.2.4. By Application 12.3. Market Attractiveness Analysis 12.3.1. By Country 12.3.2. By Technology 12.3.3. By Deployment Mode 12.3.4. By Application 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 Technology 13.2.3. By Deployment Mode 13.2.4. By Application 13.3. Market Attractiveness Analysis 13.3.1. By Country 13.3.2. By Technology 13.3.3. By Deployment Mode 13.3.4. By Application 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 Technology 14.2.3. By Deployment Mode 14.2.4. By Application 14.3. Market Attractiveness Analysis 14.3.1. By Country 14.3.2. By Technology 14.3.3. By Deployment Mode 14.3.4. By Application 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 Technology 15.2.3. By Deployment Mode 15.2.4. By Application 15.3. Market Attractiveness Analysis 15.3.1. By Country 15.3.2. By Technology 15.3.3. By Deployment Mode 15.3.4. By Application 15.4. Key Takeaways 16. Key Countries Market Analysis 16.1. USA 16.1.1. Market Share Analysis, 2023 16.1.1.1. By Technology 16.1.1.2. By Deployment Mode 16.1.1.3. By Application 16.2. Canada 16.2.1. Market Share Analysis, 2023 16.2.1.1. By Technology 16.2.1.2. By Deployment Mode 16.2.1.3. By Application 16.3. Brazil 16.3.1. Market Share Analysis, 2023 16.3.1.1. By Technology 16.3.1.2. By Deployment Mode 16.3.1.3. By Application 16.4. Mexico 16.4.1. Market Share Analysis, 2023 16.4.1.1. By Technology 16.4.1.2. By Deployment Mode 16.4.1.3. By Application 16.5. Germany 16.5.1. Market Share Analysis, 2023 16.5.1.1. By Technology 16.5.1.2. By Deployment Mode 16.5.1.3. By Application 16.6. UK 16.6.1. Market Share Analysis, 2023 16.6.1.1. By Technology 16.6.1.2. By Deployment Mode 16.6.1.3. By Application 16.7. France 16.7.1. Market Share Analysis, 2023 16.7.1.1. By Technology 16.7.1.2. By Deployment Mode 16.7.1.3. By Application 16.8. Spain 16.8.1. Market Share Analysis, 2023 16.8.1.1. By Technology 16.8.1.2. By Deployment Mode 16.8.1.3. By Application 16.9. Italy 16.9.1. Market Share Analysis, 2023 16.9.1.1. By Technology 16.9.1.2. By Deployment Mode 16.9.1.3. By Application 16.10. Poland 16.10.1. Market Share Analysis, 2023 16.10.1.1. By Technology 16.10.1.2. By Deployment Mode 16.10.1.3. By Application 16.11. Russia 16.11.1. Market Share Analysis, 2023 16.11.1.1. By Technology 16.11.1.2. By Deployment Mode 16.11.1.3. By Application 16.12. Czech Republic 16.12.1. Market Share Analysis, 2023 16.12.1.1. By Technology 16.12.1.2. By Deployment Mode 16.12.1.3. By Application 16.13. Romania 16.13.1. Market Share Analysis, 2023 16.13.1.1. By Technology 16.13.1.2. By Deployment Mode 16.13.1.3. By Application 16.14. India 16.14.1. Market Share Analysis, 2023 16.14.1.1. By Technology 16.14.1.2. By Deployment Mode 16.14.1.3. By Application 16.15. Bangladesh 16.15.1. Market Share Analysis, 2023 16.15.1.1. By Technology 16.15.1.2. By Deployment Mode 16.15.1.3. By Application 16.16. Australia 16.16.1. Market Share Analysis, 2023 16.16.1.1. By Technology 16.16.1.2. By Deployment Mode 16.16.1.3. By Application 16.17. New Zealand 16.17.1. Market Share Analysis, 2023 16.17.1.1. By Technology 16.17.1.2. By Deployment Mode 16.17.1.3. By Application 16.18. China 16.18.1. Market Share Analysis, 2023 16.18.1.1. By Technology 16.18.1.2. By Deployment Mode 16.18.1.3. By Application 16.19. Japan 16.19.1. Market Share Analysis, 2023 16.19.1.1. By Technology 16.19.1.2. By Deployment Mode 16.19.1.3. By Application 16.20. South Korea 16.20.1. Market Share Analysis, 2023 16.20.1.1. By Technology 16.20.1.2. By Deployment Mode 16.20.1.3. By Application 16.21. GCC Countries 16.21.1. Market Share Analysis, 2023 16.21.1.1. By Technology 16.21.1.2. By Deployment Mode 16.21.1.3. By Application 16.22. South Africa 16.22.1. Market Share Analysis, 2023 16.22.1.1. By Technology 16.22.1.2. By Deployment Mode 16.22.1.3. By Application 16.23. Israel 16.23.1. Market Share Analysis, 2023 16.23.1.1. By Technology 16.23.1.2. By Deployment Mode 16.23.1.3. By Application 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 Technology 17.3.3. By Deployment Mode 17.3.4. By Application 18. Competition Analysis 18.1. Competition Deep Dive 18.1.1. Amazon Web Services, Inc 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. BlackRock, Inc 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. CapitalG 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. Charles Schwab & Co., Inc 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. Genpact 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. Infosys Limited 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. International Business Machines Corporation 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. IPsoft Inc 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. Microsoft 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 18.1.10. Salesforce, Inc. 18.1.10.1. Overview 18.1.10.2. Product Portfolio 18.1.10.3. Profitability by Market Segments 18.1.10.4. Sales Footprint 18.1.10.5. Strategy Overview 18.1.10.5.1. Marketing Strategy 19. Assumptions & Acronyms Used 20. Research Methodology
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