Artificial Intelligence (AI) in Asset Management Market Report 2025

The artificial intelligence (AI) in asset management market size has grown exponentially in recent years. It will grow from $4.19 billion in 2024 to $5.41 billion in 2025 at a compound annual growth rate (CAGR) of 29%. The growth in the historic period can be attributed to advancements in data analytics, quantitative analysis development, increasing complexity of financial markets, risk management needs, algorithmic trading.

The artificial intelligence (AI) in asset management market size is expected to see exponential growth in the next few years. It will grow to $16.53 billion in 2029 at a compound annual growth rate (CAGR) of 32.2%. The growth in the forecast period can be attributed to ai-powered investment decision making, enhanced portfolio optimization, alternative data integration, regulatory compliance solutions, global economic volatility. Major trends in the forecast period include explainable ai models, ai-driven esg integration, predictive analytics, ai in wealth management, expansion of robo-advisors.

The increasing adoption of cloud solutions across various industries is significantly contributing to the growth of artificial intelligence (AI) in the asset management market. Cloud solutions refer to the delivery of a range of services over the Internet, including networking, servers, databases, software, and data storage. Asset management firms utilize cloud solutions to access AI software, helping to improve asset utilization and optimize asset distribution. For instance, in December 2023, according to Eurostat, a Luxembourg-based Directorate-General of the European Commission, 45.2% of EU enterprises purchased cloud computing services in 2023, marking a 4.2 percentage point increase from 2021. Countries like Finland (78.3%), Sweden (71.6%), and Denmark (69.5%) were leaders in cloud service purchases. As a result, the growing adoption of cloud solutions across industries is driving AI in the asset management market.

The growing need for advanced fraud detection solutions is also expected to boost the growth of AI in the asset management market. Fraud detection involves identifying and preventing fraudulent activities or behaviors within a system or organization. The integration of AI in asset management enhances fraud detection by increasing efficiency, accuracy, early detection of anomalies, real-time monitoring, analysis of user behavior and transaction patterns, and adaptability to evolving financial security threats. For example, in February 2023, according to Check Point Software Technologies Ltd., a US-based provider of cybersecurity solutions to corporations and governments, cyberattacks increased by 38% in 2022 compared to the previous year, with organizations experiencing an average of 1,168 weekly attacks. Thus, the rising demand for advanced fraud detection solutions is fueling the growth of AI in the asset management market.

Product innovation stands as the predominant trend gaining traction within the artificial intelligence (AI) in asset management sector. Notably, major industry players are directing their efforts towards crafting advanced AI platforms capable of automating essential asset management functions to reinforce their market standing. For instance, in May 2023, Aisot Technologies, a Switzerland-based software company, unveiled a fully automated platform tailored for active asset management. This tool empowers asset managers to curate portfolios that dynamically reflect consumer preferences across stock and cryptocurrency markets. Moreover, it streamlines the creation of fully automated financial products from investment decisions while harnessing artificial intelligence for optimization. Distinguished by its utilization of AI, neuro-linguistic programming, and quantitative finance, this platform marks a pioneering move by offering services catering to both traditional assets and the cryptocurrency domain.

Significant entities within the AI-driven asset management arena are actively developing novel products, such as next-generation AI supercomputing services, to carve a competitive edge in the market. AI supercomputing services encompass cloud-based or specialized computing services optimized specifically for high-performance artificial intelligence workloads. For example, in March 2023, NVIDIA Corporation, a prominent US-based technology company, introduced DGX Cloud. DGX Cloud presents businesses with seamless access to NVIDIA's AI supercomputing capabilities via a web browser from various global cloud platforms. Functioning as an AI-training-as-a-service platform, DGX Cloud furnishes enterprise developers with a serverless environment specifically tailored for generative AI tasks. Offering businesses the ability to access their personalized AI supercomputer via standard web browsers, DGX Cloud instances boast eight NVIDIA 80GB Tensor Core GPUs, delivering 640GB of GPU memory per instance.

In April 2023, Alarm.com, a prominent US-based home automation company, successfully acquired Vintra for an undisclosed amount. Through this acquisition, Alarm.com aims to enhance its deep learning program and accelerate the implementation of advanced video analytics solutions for both the Alarm.com and OpenEye platforms. Vintra, the acquired company, is based in the United States and specializes in artificial intelligence (AI) video analytics. It provides solutions for home asset management through the application of video analytics technologies.

Major companies operating in the artificial intelligence (AI) in asset management market include Alphabet Inc., Microsoft Corporation, JPMorgan Chase & Co., Amazon Web Services Inc., International Business Machines Corporation, Deloitte Touche Tohmatsu Ltd., The Goldman Sachs Group Inc., UBS Group AG, Salesforce Inc., FMR LLC, BlackRock Inc., Infosys Limited, S&P Global Inc., Franklin Templeton Distributors Inc., Invesco Ltd., Genpact LLC, Schroders plc, Man Group Ltd., Wellington Management Company LLP, Janus Henderson Group Plc, Robeco B.V., Bridgewater Associates LP, Winton Group Limited, D.E. Shaw & Co., AQR Capital Management LLC, Renaissance Technologies LLC, Dimensional Fund Advisors LP, Eaton Vance Corp.

North America was the largest region in the artificial intelligence (AI) in asset management market in 2024. The regions covered in the artificial intelligence (ai) in asset management market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the artificial intelligence (ai) in asset management market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Italy, Spain, Canada.

Artificial intelligence (AI) in asset management involves the utilization of AI technologies to automate the management of a company's inventory and assets. Employing AI in asset management allows businesses to monitor their investments with precision, eliminating the possibility of human error and the need for manual data input.

The primary technologies associated with artificial intelligence in asset management include machine learning, deep learning, natural language processing, predictive analytics, and others. Machine learning is an AI application comprising algorithms that analyze data, learn from it, and apply acquired knowledge to make intelligent decisions. Deep learning, on the other hand, is a subset of machine learning that involves organizing algorithms in layers to create an artificial neural network capable of independent learning and decision-making. These AI technologies are deployed in both on-premises and cloud infrastructure, serving various applications such as portfolio optimization, risk and compliance management, process automation, conversational platforms, data analysis, and more. Industries benefiting from AI in asset management include BFSI (banking, financial services, and insurance), healthcare, retail and e-commerce, media and entertainment, energy and utilities, automotive, among others.

The artificial intelligence (AI) in asset management research report is one of a series of new reports that provides artificial intelligence (AI) in asset management market statistics, including the artificial intelligence (AI) in asset management industry's global market size, regional shares, competitors with artificial intelligence (AI) in asset management market share, detailed artificial intelligence (AI) in asset management market segments, market trends and opportunities, and any further data you may need to thrive in the artificial intelligence (AI) in asset management industry. This artificial intelligence (AI) in asset management market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenarios of the industry.

The artificial intelligence (AI) in asset management market consists of revenues earned by entities by providing services such as portfolio distribution services, asset tracking services and asset analysis services. The market value includes the value of related goods sold by the service provider or included within the service offering. The artificial intelligence (AI) in asset management market also includes sales of workstations, drives, routers, and servers, which are used in providing artificial intelligence (AI) in asset management services. Values in this market are ‘factory gate’ values, that is the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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