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The Artificial Intelligence (AI) in Asset Management Market size is estimated to grow by USD 26.91 billion at a CAGR of 53.95% between 2032 and 2028. The market is driven by factors such as the swift integration of artificial intelligence in asset management and the escalating significance of asset tracking. Additionally, the mounting requirement to adhere to asset management standards and the expansion of managed IT infrastructure play pivotal roles. These factors collectively contribute to the market's expansion and underscore the increasing reliance on advanced technologies for efficient asset management. The adoption of artificial intelligence has revolutionized asset management practices, enhancing their accuracy and efficiency. Similarly, the emphasis on asset tracking has become more pronounced, driven by the need for precise monitoring and management of assets. Compliance with standards has also become imperative, reflecting the industry's commitment to best practices and regulatory requirements. Lastly, the expansion of IT infrastructure has facilitated the adoption of sophisticated asset management solutions such as digital asset management, further propelling market growth.
The market research report provides comprehensive data (region wise segment analysis), with forecasts and estimates in "USD Billion" for the period 2024 to 2028, as well as historical data from 2018- 2022 for the following segments.
The market share growth by the on-premises segment will be significant during the forecast period. The on-premise segment in the market is expected to witness significant growth in the coming years. On-premise artificial intelligence solutions give organizations greater data control and flexibility than cloud-based solutions. These solutions are installed locally on your company's servers and tailored to your specific business needs. One of the key benefits of on-premises artificial intelligence solutions is that organizations have complete control over their data. Because the software is installed on your organization's servers, it can be customized to meet your organization's unique needs. This level of customization is not possible with cloud-based solutions designed to serve a wide range of customers with standardized functionality.
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The on-premises segment was valued at USD 601.00 million in 2018. On-premises solutions offer better security because information is stored on corporate premises rather than on remote cloud servers. This eliminates the risk of data breaches and ensures sensitive company information is protected. Additionally, on-premises solutions have better performance and faster response times because the information is processed locally on the company's servers. This enables organizations to gain more accurate and actionable insights, enabling better decision-making. For example, the investment management industry are increasingly interested in on-premises artificial intelligence solutions for wealth management. Banks and other financial institutions, in particular, deal with large amounts of sensitive information every day. To effectively manage this information, on-premises solutions provide the necessary level of customization and security. Therefore, the increase and advancement of on-premises capabilities are expected to drive the growth of the segment during the forecast period.
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North America is estimated to contribute 48% to the growth of the global market during the forecast period. Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period. With the rapid adoption of advanced technologies in the wealth management industry, North America dominates the global artificial intelligence in the wealth management market. The region is expected to claim market dominance due to the presence of established players in the region and rising demand for AI-based solutions and services. One of the major drivers of artificial intelligence in the North American wealth management market is the growing need for automation and digitization in the wealth management industry. A growing number of asset managers in the region are leveraging advanced technologies such as AI to improve their operations and better serve their customers.
Further, another factor driving the growth of artificial intelligence in the North American wealth management market is the increasing availability of information and the need for advanced analytics. Today's management firms can collect large amounts of data from various sources such as social media analytics, news articles, financial reports, and other sources. AI-based solutions can help these companies process and analyze this information more efficiently, allowing them to make better investment decisions and improve overall performance. North America has several major players in the market. All these factors are expected to drive the growth of the market in North America during the forecast period.
The market is rapidly evolving with advancements in artificial intelligence (AI), particularly in conversational platforms and chatbots. Both business-to-consumer and business-to-business sectors are embracing AI for improved services. Despite strict regulations and low-interest rates, FinTech companies are leveraging AI for enhanced NLP capabilities, exemplified by The TIFIN AMP platform. These technologies enable asset managers to refine their business strategies and deliver superior financial services and investment services. Companies like TIFIN Group are developing sophisticated algorithmic models and software platforms, enhancing operational efficiency and client retention through improved human-machine interaction systems and deep learning. In the market, Generative AI and Machine Learning (ML) are transforming investment management by enhancing predictive capabilities and optimizing portfolio management. Investment managers and portfolio managers are leveraging AI models for valuation, strategy development, and decision making, driving sustainability and resilience in the fund management industry. This shift supports equity strategy, improves returns for investors, and aligns with evolving climate change and diversity values. Technology insights from AI asset management platforms enable agility and innovation, enhancing financial markets and businesses globally. The integration of Natural Language Processing and analytics providers strengthens capital growth, assuring purpose-driven development for non-residents and stock valuation across portfolios.
The rapid adoption of artificial intelligence in IT asset management and the growing importance of asset tracking is notably driving the market. Artificial intelligence is increasingly being used in asset management, revolutionizing the industry. This technology uses complex algorithms to analyze and interpret large amounts of data in real-time, enabling asset managers to make faster, more informed investment decisions. With AI, these managers can indeed easily track asset performance and make data-driven decisions to optimize asset allocation and reduce risk. This technology enables them to develop business strategies and investment services that enhance operational efficiency. Deep learning algorithms play a crucial role in analyzing vast amounts of information to provide valuable insights for asset management.
Moreover, artificial intelligence algorithms can analyze data to identify trends and patterns that humans might miss, such as correlations between prices and economic indicators. Wealth managers can use these insights to develop more effective investment strategies. Artificial intelligence is also changing the way assets are tracked and managed. With IoT, assets can be equipped with sensors and other devices that collect information about their condition, location, and usage. This data feeds into artificial intelligence algorithms that provide real-time insights into asset health, availability, and utilization. This enables asset managers to optimize asset utilization, minimize downtime, reduce costs, and maximize revenue. Many such advancements in these are expected to drive market growth during the forecast period.
The growing adoption of cloud-based artificial intelligence services in enterprise asset management is the primary trend in the market growth. Asset management is an important part of any business and recent technological advances have led wealth managers to increasingly turn to cloud-based artificial intelligence services to improve their efficiency and decision-making capabilities. Cloud-based artificial intelligence services are growing in popularity among asset managers due to their cost efficiency and scalability. These services enable managers to process large amounts of data, identify patterns and trends, and make decisions based on real-time information. With the help of AI, wealth managers can quickly analyze economic data, market trends, and other variables that affect investments. Artificial intelligence models also help optimize portfolios by identifying the most profitable investments.
Further, by proactively managing risk, wealth managers can minimize losses and protect their clients' investments. Another advantage of cloud-based artificial intelligence services is that they can be customized to meet the needs of different asset managers. Artificial intelligence models can be designed to reflect specific investment strategies, risk profiles, and other business needs. This means asset managers can tailor artificial intelligence services to their specific needs and use them as a competitive advantage. One of the factors driving the adoption of cloud-based artificial intelligence in asset management is the increased availability of data. Asset managers have large amounts of data at their disposal, including economic indicators, financial reports, and other relevant sources of information. Cloud-based artificial intelligence services quickly process this data and provide wealth managers with real-time insights that can be used in making investment decisions. Therefore, the above factors are expected to drive the growth of AI in the asset management market during the forecast period.
The rising number of data privacy and cybersecurity is a major challenge impeding the growth of the market. The market has experienced significant growth in recent years. While artificial intelligence technology offers many benefits for asset management firms, it also raises significant privacy and cybersecurity concerns. One of the main concerns is the use of personal and confidential data. Wealth management firms rely on big data sets to make decisions, and such data sets are necessary for artificial intelligence algorithms to work. However, ensuring the privacy of such data can be difficult. As artificial intelligence algorithms continue to advance, access to more detailed information about individuals and their financial history will be required. If such data is not properly protected, it can become a target for cybercriminals.
However, another issue is the use of external data sources, which can lead to data access and ownership issues. When artificial intelligence systems rely on such data sources, it can be difficult to verify data processing and determine information ownership. There have been instances of data sources being hacked and third parties gaining unauthorized access to and using the data. In addition, asset management companies must ensure that security systems are in place to protect against cyberattacks and data breaches. As artificial intelligence systems are integrated into business operations, they become more vulnerable and require specific cybersecurity and privacy safeguards.
Also, the use of artificial intelligence may automate certain tasks that were previously performed by humans. While this increases productivity and efficiency, it can also lead to job losses. Loss of potential employment opportunities is an issue asset management firms must address. Finally, the issue of regulatory compliance remains a major challenge. Various laws and regulations in various jurisdictions governing data protection, cybersecurity, and the use of artificial intelligence make it difficult for wealth management firms to navigate the compliance landscape. Therefore, an increasing number of cyber-attacks and data breaches may impede AI in asset management market growth during the forecast period.
The Asset Management market analysis report includes the adoption lifecycle of the market, covering from the innovator's stage to the laggard's stage. It focuses on adoption rates in different regions based on penetration. Furthermore, the Asset Management market size report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Global Market Customer Landscape
Companies are implementing various strategies, such as strategic alliances, partnerships, mergers and acquisitions, geographical expansion, and product/service launches, to enhance their presence in the market.
Amazon.com Inc.: The company offers artificial intelligence asset management services through Amazon Web services.
The Asset Management market growth insights analysis report also includes detailed analyses of the competitive landscape of the market and information about 15 market companies, including:
Qualitative and quantitative analysis of companies has been conducted to help clients understand the wider business environment as well as the strengths and weaknesses of key market players. Data is qualitatively analyzed to categorize companies as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize companies as dominant, leading, strong, tentative, and weak.
The assets management market report witnessing significant advancements driven by computer vision and voice recognition programs. With the rise of digital workspace and WFH trends, technologies like aerial imagery and virtual assistants are gaining traction. Despite challenges such as low interest rates and data volumes, AI algorithms, and machine learning are revolutionizing risk management, portfolio optimization, and compliance monitoring. Digital technology and AI models are enhancing investor protection and ethical thinking in decision-making processes. Companies like Scotia Smart Investor and EagleView are leveraging AI for financial transactions and investment processes, improving data quality, and optimizing business metrics through Chabot and other innovative solutions.
Furthermore, the market is evolving with advancements in big data analytics and data analysis, enhancing decision-making in the face of market volatility. The industry is leveraging AI for digital interactions and processing vast amounts of financial data, including company announcements and newspapers to identify market inefficiencies. Quantitative modeling and alpha generation techniques are being refined using historical trading data, driving innovation in the asset management industry. Technology companies and analytics providers play a crucial role, offering AI models and resources to optimize alpha generation and improve overall asset management efficiency by fund managers.
Market Scope |
|
Report Coverage |
Details |
Page number |
167 |
Base year |
2023 |
Historic period |
2018 - 2022 |
Forecast period |
2024-2028 |
Growth momentum & CAGR |
Accelerate at a CAGR of 53.95% |
Market growth 2024-2028 |
USD 26.91 billion |
Market structure |
Fragmented |
YoY growth 2023-2024(%) |
39.44 |
Regional analysis |
North America, Europe, APAC, Middle East and Africa, and South America |
Performing market contribution |
North America at 48% |
Key countries |
US, China, Germany, UK, and France |
Competitive landscape |
Leading Companies, Market Positioning of Companies, Competitive Strategies, and Industry Risks |
Key companies profiled |
Amazon.com Inc., AXOVISION GmbH, BlackRock Inc., Deloitte Touche Tohmatsu Ltd., Genpact Ltd., Infosys Ltd., International Business Machines Corp., Lexalytics Inc., Microsoft Corp., New Narrative Ltd., Salesforce Inc., and The Charles Schwab Corp. |
Market dynamics |
Parent market analysis, Market growth inducers and obstacles, Fast-growing and slow-growing segment analysis, Market growth and Forecasting, COVID 19 impact and recovery analysis and future consumer dynamics, Market condition analysis for the market forecast period |
Customization purview |
If our report has not included the data that you are looking for, you can reach out to our analysts and get segments customized. |
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1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation by Deployment
7 Market Segmentation by Application
8 Customer Landscape
9 Geographic Landscape
10 Drivers, Challenges, and Opportunity/Restraints
11 Competitive Landscape
12 Competitive Analysis
13 Appendix
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