PUBLISHER: Orion Market Research | PRODUCT CODE: 1565756
PUBLISHER: Orion Market Research | PRODUCT CODE: 1565756
Artificial Intelligence (AI) In Asset Management Market Size, Share & Trends Analysis Report by Technology (Machine Learning, Natural Language Processing (NLP), and Others), by Deployment Mode (On-Premises, and Cloud) and by Application (Portfolio Optimization, Conversational Platform, Risk & Compliance, Data Analysis, Process Automation, and Others) Forecast Period (2024-2031)
AI in the asset management market is anticipated to grow at a CAGR of 38.1% during the forecast period (2024-2031). AI in asset management is gaining popularity owing to its ability to process large amounts of data, predict market trends, optimize portfolios, and provide personalized investment solutions. AI aids in portfolio optimization, risk management, compliance monitoring, and reporting, ensuring cost efficiency and scalability.
Market Dynamics
Growing demand for digitalization
The increasing adoption of digital technology, the complexity of data, and the demand for sustainable, efficient practices particularly in offshore operations are all driving substantial changes in the global AI asset management market. For instance, in March 2024, Imrandd launched an AI-powered asset management solution for offshore operators. The AI-powered asset management solution, ALERT, reduces inspection time and costs for offshore operators. The £1 million ($1.3 million) investment, supported by funding from the Net Zero Technology Centre, allows real-time monitoring of corrosion threats and provides real-time insights into asset performance.
Increasing demand for specialized investment solutions
The widespread adoption of AI in asset management is being driven by the growing demand for personalized and sustainable investment solutions that align with investors' values. AI's ability to generate vast numbers of investment strategies has the potential to revolutionize asset management. For instance, in September 2021, Arabesque introduced autonomous asset management (AutoCIO), powered by its proprietary AI Engine. This technology allows for the creation of highly customized active equity strategies tailored to investors' sustainability objectives and values. It can forecast stock performance on 25,000 equities daily and generate millions of active equity investment strategies. Over $400million of investment strategies are successfully powered by AutoCIO.
Market Segmentation
Machine Learning is Projected to Emerge as the Largest Segment
The primary factor supporting the segment's growth includes the advancements in machine learning. The adoption of machine learning-integrated next-generation asset management solutions offers enhanced comprehension of asset performance and foster efficiency and innovation which in turn drives the growth of this market segment. For instance, in February 2023, EagleView launched next-generation asset management solutions, combining high-resolution aerial imagery with machine learning. These solutions help local governments and commercial organizations manage assets accurately, automate data collection and analysis, and identify trends in asset performance, enabling prioritization of maintenance and repair work.
Risk & Compliance Sub-segment to Hold a Considerable Market Share
Management firms are adopting AI risk policies to uphold regulatory compliance, safeguard retail clients, and maintain the integrity of financial markets. To integrate AI in asset management for risk & compliance, key players are introducing advanced products. For instance, in February 2024, Behavox expanded its AI risk policies for wealth and asset management firms with retail client bases. The enhanced policies detect compliance issues like sales suitability, unfair communications, window dressing, and cherry-picking. The company additionally enhanced detection capabilities for customer complaints, money laundering, personal financial dealings, sub-optimal execution, churning, misappropriation of client assets, unauthorized trading in client accounts, and tax evasion.
The Artificial intelligence (AI) in the asset management market is further segmented based on geography including North America (the US, and Canada), Europe (UK, Italy, Spain, Germany, France, and the Rest of Europe), Asia-Pacific (India, China, Japan, South Korea, and Rest of Asia-Pacific), and the Rest of the World (the Middle East & Africa, and Latin America).
Investments in AI In the Asia-Pacific Region
The expansion in asset management has been attributed to the significant rise in investments in AI. For instance, in March 2023, Accenture acquired Bangalore-based industrial AI company Flutura, aiming to enhance its services in various industries, including energy, chemicals, metals, mining, and pharmaceuticals, to achieve net zero goals.
North America Holds Major Market Share
The use of AI in asset management is increasing across the region due to the increasing demand of US investors for innovative techniques for better results while utilizing investments in assets in competitive markets. For instance, in February 2024, Vanguard Group integrated AI into its active equity funds, including four-factor funds with 13 billion assets under management. These funds, which include the Vanguard Global Minimum Volatility Fund, Vanguard Global Value Factor Fund, Vanguard Global Momentum Factor Fund, and Vanguard Global Liquidity Factor Fund, combine various factors with variable weightings.
The major companies serving AI in asset management market include IBM Corp., Infosys Ltd., Microsoft Corp., S&P Global Inc., and State Street Corp. among others. The market players are increasingly focusing on business expansion and product development by applying strategies such as collaborations, mergers and acquisitions to stay competitive in the market. For instance, in February 2023, TIFIN, partnered with Morningstar to provide real-time industry trend information for its asset manager platform (AMP). This enabled asset managers to modernize the distribution to non-institutional and retail audiences, enabling them to better understand the consumption of investment products and generate new insights.