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The Artificial Intelligence (AI) in Asset Management Market size is estimated to grow at a CAGR of 37.88% between 2022 and 2027. The market size is forecast to increase by USD 10,373.18 million. The growth of the market depends on several factors, including the rapid adoption of artificial intelligence in asset management and the growing importance of asset tracking, the increasing need to comply with asset management standards, and the expansion of IT infrastructure.
This Artificial Intelligence (AI) in Asset Management Market report extensively covers market segmentation by deployment (on-premises and cloud), industry application (BFSI, retail and e-commerce, healthcare, energy and utilities, and others), and geography (North America, Europe, APAC, Middle East and Africa, and South America). It also includes an in-depth analysis of drivers, trends, and challenges. Furthermore, the report includes historic market data from 2017 to 2021.
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The rapid adoption of artificial intelligence in asset management and the growing importance of asset tracking is notably driving the market growth, although factors such as the rising number of data privacy and cybersecurity may impede the market growth. Our researchers analyzed the data with 2022 as the base year, along with the key drivers, trends, and challenges. A holistic analysis of drivers will help companies refine their marketing strategies to gain a competitive advantage.
The rapid adoption of artificial intelligence in asset management and the growing importance of asset tracking is notably driving the Artificial Intelligence in Asset Management 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, asset managers can easily track asset performance and make data-driven decisions to optimize asset allocation and reduce risk.
Artificial intelligence algorithms can analyze data to identify trends and patterns that humans might miss, such as correlations between asset 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 data 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 asset management are expected to drive AI in asset management market growth during the forecast period.
Growing adoption of cloud-based artificial intelligence services in asset management is the primary trend in the global artificial intelligence (AI) in asset management 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 asset 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.
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 global artificial intelligence (AI) in the asset management market. The global artificial intelligence in asset management 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.
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, increasing number of cyber-attacks and data breaches may impede AI in asset management market growth during the forecast period.
The 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 report also includes key purchase criteria and drivers of price sensitivity to help companies evaluate and develop their growth strategies.
Global Artificial Intelligence in Asset Management Market Customer Landscape
Vendors 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 report also includes detailed analyses of the competitive landscape of the market and information about 15 market vendors, including:
Qualitative and quantitative analysis of vendors 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 vendors as pure play, category-focused, industry-focused, and diversified; it is quantitatively analyzed to categorize vendors as dominant, leading, strong, tentative, and weak.
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 472.84 million in 2017 and continued to grow until 2021. On-premises solutions offer better security because data 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 data is processed locally on the company's servers. This enables organizations to gain more accurate and actionable insights, enabling better decision-making. For example, financial institutions 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 data every day. To effectively manage this data, 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 49% 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.
Another factor driving the growth of artificial intelligence in the North American wealth management market is the increasing availability of data and the need for advanced analytics. Today's asset management firms can collect large amounts of data from various sources such as social media, news articles, financial reports, and other sources. AI-based solutions can help these companies process and analyze this data more efficiently, allowing them to make better investment decisions and improve overall performance. North America has several major players in the artificial intelligence space in the asset management market. All these factors are expected to drive the growth of artificial intelligence in the asset management market in North America during the forecast period.
This report forecasts the contribution of all the segments to the growth of the market. In addition, we have included the COVID-19 impact and the recovery strategies for each segment. Artificial intelligence in the asset management market in North America slowed down in 2020 due to the COVID-19 outbreak. Due to the 2020 pandemic, some end-user sectors, such as small and medium enterprises (SMEs) and large enterprises, have partially stopped operations, and various SMEs had stopped their operations, thus reducing the use of AI. However, various IT companies have provided telecommuting facilities for their employees and have gradually decided to introduce cloud-based artificial intelligence in asset management to manage remote workers from the first half of 2020. However, with the resumption of normal business operations in late 2020 and early 2021, the demand for on-premises artificial intelligence in asset management has increased. This is expected to drive the growth of regional artificial intelligence in the wealth management market during the forecast period.
The artificial intelligence in asset management market report forecasts market growth by revenue at global, regional & country levels and provides an analysis of the latest trends and growth opportunities from 2017 to 2027.
Technavio categorizes global artificial intelligence in asset management market as a part of the global systems software market within the global information technology (IT) software market. The super parent market, global IT software, covers companies engaged in developing and producing application and systems software. It also includes companies offering database management software. The global systems software market covers organizations that are engaged in developing application development and management software, cloud computing software, data center, hosting software, IT management software, mobility software, networking software, security software, and storage software. It excludes companies classified in the development and production of home entertainment software. Our market research report has extensively covered external factors influencing the parent market growth during the forecast period.
Artificial Intelligence In Asset Management Market Scope |
|
Report Coverage |
Details |
Page number |
162 |
Base year |
2022 |
Historic period |
2017-2021 |
Forecast period |
2023-2027 |
Growth momentum & CAGR |
Accelerate at a CAGR of 37.88% |
Market growth 2023-2027 |
USD 10,373.18 million |
Market structure |
Concentrated |
YoY growth 2022-2023(%) |
35.12 |
Regional analysis |
North America, Europe, APAC, Middle East and Africa, and South America |
Performing market contribution |
North America at 49% |
Key countries |
US, China, Germany, UK, and France |
Competitive landscape |
Leading Vendors, Market Positioning of Vendors, 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, COVID-19 impact and recovery analysis and future consumer dynamics, and market condition analysis for the 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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