AI in Asset Management Market Size - By Technology, By Deployment Model, By Application, By End Use, Analysis, Share, Growth Forecast, 2025 - 2034

AI in Asset Management Market Size

The AI in asset management market was valued at USD 3.4 billion in 2024 and is projected to grow at a CAGR of 24.2% between 2025 and 2034. The rapidly increasing volume of data, stringent regulations, and low interest rates continue to force asset managers to reassess their conventional business practices. The most recent advancements in technology also provide an avenue for further specialization in asset management. Numerous Fintech companies are utilizing knowledge-enhanced, domain-centric machine learning and Natural Language Processing (NLP) technologies to offer a wide range of financial and investment services.
 

For example, Statista claims that the amount of data produced, captured, or used worldwide is set to increase at a staggering rate to reach 149 zettabytes by 2024. Within the subsequent five years, the amount of global data produced is anticipated to surpass 394 zettabytes by 2028. To process and analyze this massive scale of data for asset management, modern technologies are necessary. This demand for data drives AI in asset management markets.

The rapid adoption of AI in the asset management sector is further fueled by strong government initiatives that encourage financial industry transformation through investment in AI-driven infrastructure. There are ongoing efforts in many countries to spend on AI research, formulate smart regulations, and develop AI-powered fintech ecosystems, which will entice asset managers to apply AI in their investment strategies. Policies that bolster the development of cloud computing, big data, and AI specialists encourage the use of AI in finance institutions.
 

For example, Saudi Arabia sought to make a considerable investment in AI in March 2024 by setting up a proposed $40 billion fund, which will help the country in its overall economic diversification strategy under Vision 2030. This investment aligns with Saudi Arabia’s vision to become one of the largest investors in AI globally and a central activity hub for AI outside of the US.
 

AI in Asset Management Market Trends

• All financial institutions and investment firms are adopting robo-advisors with AI technology to automate, personalize, and deliver cost-effective investment services. AI is being adopted rapidly in the asset management sector as machine learning and prediction analytics are utilized to optimize portfolios and maximize client satisfaction.
   
• As per Statista, the robo-advisor sector is expected to manage assets amounting to US 2.06 trillion by 2025. Additionally, this industry is also set to have approximately 34 million registered users by 2029. This growth has a direct effect on the AI asset management industry and fosters the growth of the industry.
   
• AI algorithms scan through historical data, currently available data, and real-time general economic trends and formulate future risks for investment portfolios. This permits firms to continuously change their asset allocations to counterbalance uncertainty and losses. Predictive analytics also aid in risk management by allowing asset managers to better anticipate potential changes in the market.
   
• According to Statista, predictive analytics software had a market cap of 5.29 billion US dollars as of 2020 and it is expected to increase to 41.52 billion US dollars by 2028. Such analytics have a positive effect on the AI in asset management and will stimulate the growth of the industry.
   

AI in Asset Management Market Analysis

Based on technology, the AI in asset management market is divided into Machine Learning (ML) and Natural Language Processing (NLP). In 2024, the Machine Learning (ML) segment dominated the market generating revenue of over USD 2 billion and the Machine Learning (ML) segment is expected to grow at a CAGR of around 23.8% during the forecast period.
 

• Currently modern business uses ML to spot patterns as well as for refining modeling and alpha generation procedures. ML algorithms are trained on trading history to pinpoint certain events or indicators that can produce above-average returns. Portfolio optimization, risk assessment, fraud detection, and algorithmic trading are enhanced by machine learning, and positioning asset managers to improve productivity and minimize human errors.
   
• NLP tools further elucidate sentiment analysis and fraud predictions while enabling more effective real-time market evaluation and movements. With the help of NLP the generation of reports, communication with clients through chatbots, and monitoring of compliance becomes automated in financial institutions, enhancing productivity and accuracy.
   
• The size of the global market for Natural Language Processing (NLP) in Finance is projected to be valued at over USD 5.5 billion in 2023, with an expected CAGR rate of over 25% from 2024 to 2032. The expansion of the NLP in finance market will in turn boost the market.
   

Based on the deployment model, the AI in asset management market is segmented into on-premises and cloud-based. In 2024, the on-premises segment dominates the market with 60% of market share and the frozen segment is expected to grow at a CAGR of over 23% from 2025 to 2034.
 

• Among various deployment models, on-premises maintenance and deployment has the highest market share in artificial intelligence in asset management because of the unmatched security, flexibility, and compliance capabilities. Firms engaged in asset management have highly sensitive financial information, which makes data privacy and cybersecurity a primary concern. Financial firms are also burdened by strict obligations on spending, therefore, on-premises AI solutions give an firm control over their infrastructure.
   
• For example, in February 2025 ANYbotics released a new asset management product called Data Navigator that converts inspection data gathered by its ANYmal quadruped robots into useful information. With this platform, companies can improve asset health evaluation and execute condition-based maintenance in areas like energy, metals, mining, and oil and gas.
   

Based on the application, the AI in asset management market is segmented into portfolio optimization, conversational platform, risk & compliance, data analysis, process automation, and others, with the portfolio optimization category expected to dominate due to its crucial role in enhancing investment performance and risk management.
 

• AI-enabled portfolio optimization allows asset managers to view and analyze as well as interpret vast datasets. As a result, it can help managers make timely investments that are informed by real-time data patterns. To derive and suggest optimal asset allocations, maximum returns, and exposure, machine learning algorithms assess market conditions, historical performance, and risk exposure.
   
• For example, in February 2025 AlphaSavings single-handedly broke into the financial services market by launching an AI-powered stock and bond investing platform. This platform leverages artificial intelligence in wealth management by providing truly hands-free investment as an account is fully managed by AI. AI makes sure that an optimal balance between stocks and bonds is always maintained regardless of economic conditions and reallocations are performed as necessary.
   

In 2024, the North America region dominated AI in asset management market with around 38% market share and generates around USD 1.3 billion in revenue.
 

• With the adoption of sophisticated tools and machine-learning based automation in making investments, the U.S. market for AI in asset management is expected to grow. Leading banks and hedge funds practice asset management, risk assessment, and trading through AI-powered automated systems. The presence of leading providers of AI technologies and fintech startups, however, drives innovation in predictive analysis and robo-advisory services development.
   
• For example, Blackrock and Microsoft partnered under the title Global Artificial Intelligence Infrastructure Investment Partnership (GAIIP) with the purpose of raising USD 30 billion in private equity capital in September 2024. This investment is part of a larger scheme that aims to eventually mobilize $100 billion.
   

The AI in asset management market in Germany is expected to experience significant and promising growth from 2025 to 2034.
 

• The market for AI in asset management in Germany is fueled by the growing use of social media analytics, algorithmic trading, and AI-enabled robo-advising among banks, investment firms, and asset managers. For example, Deutsche Bank and Allianz Global Investors are already using AI to enhance portfolio management, risk mitigation, and customer service.
   
• For instance, Big Xyt, an artificial intelligence financial market analytics company based in London, was given €10 million from Finch Capital in November 2024. This investment allowed the company to broaden its client base and service offerings in Europe, the United States, and APAC Regions. This is the first time the company has received an investment; it has been exclusively self-funded for the last ten years.
   

The AI in asset management market in China is expected to experience significant and promising growth from 2025 to 2034.
 

• Having the presence of top technology companies such as Tencent, Alibaba, and Baidu along with AI startups encourages innovation in the sector. The leading Chinese financial institutions and asset management companies have also started adopting AI technologies to improve investment decision-making, fraud detection and regulatory compliance.
   
• For instance, in January 2024, China created a brand-new investment fund that aims to fast-track developments in AI, provided it with an initial capital of 60 billion yuan (or around $8.2 billion). This is part of a bigger plan to improve China’s standing with AI and other technologies worldwide.
   

The AI in asset management market in Saudi Arabia is expected to experience significant and promising growth from 2025 to 2034.
 

• Saudi Arabia already adopted many modern technologies, which is why the market for AI in asset management is emerging. Government initiatives such as Vision 2030 encourage the adoption of AI in banking and investment services. These initiatives also create a need for automated tools for portfolio management and risk assessment. Businesses like Saudi Aramco Investment Management and Riyad Bank are using AI for predictive analytics and robo-advisory services.
   
• For example, in February 2025, the country surpassed all previous records during the LEAP 2025 conference in Riyad by obtaining USD 14.9 billion worth of investments in AI. Such investment positions Saudi Arabia distinctly on the global scene as a rapidly developing country in AI, cloud computing, and other digital utilities.
   

AI in Asset Management Market Share

• Top 7 companies of the AI in asset management industry are Amazon Web Services, Microsoft, IBM, Intel, Infosys, Genpact, and Accenture holding around 49% of the market in 2024.
   
• Asset management is powered by AI technologies at AWS through products such as Amazon Lookout for Equipment and AWS IoT. The firm's machine learning model improves predictive maintenance and anomaly detection operational efficiency. AI in conjunction with digital twins and real-time analytics enables firms to effectively manage the asset lifecycle and downtime. Its penetration into the industrial sector makes its asset management reach deeper.
   
• With Microsoft, industries leveraging AI will take advantage of Azure AI and IoT solutions to increase predictive maintenance and asset performance management. Real-time monitoring along with failure forecast and operational insights are made possible with the help of Azure Machine Learning and Digital Twins. The organization further extends the use of intelligence and automation analytics into enterprise asset management systems (EAM) and partners with the manufacturing, and energy industries for better asset tracking and life cycle management.
   
• IBM makes use of its AI powered asset management tool, the Maximo Application Suite, enabled for asset management. Synchronized IoT AI and analytics work towards predictive maintenance and risk management. Watson AI supports better real-time insights, enhanced detection of anomalies, and optimization of assets. Also, IBM is keen on AI process automation to cut down operating expenses while increasing the overall asset life. They partner with utilities and transport industries to implement scalable AI based asset management solutions.
   

AI in Asset Management Market Companies

Major players operating in the AI in asset management industry are:

• Accenture
• Amazon Web Services
• Charles Schwab & Co
• Genpact
• IBM
• Infosys
• Intel Corporation
• Microsoft
• S&P Global
• Salesforce
   

The leading companies in the marketplace utilize numerous opportunities, for example building partnerships or collaboratives, mergers and acquisitions, new launches along with the innovations of existing ones and investment in further research and development. It also aids in the holistic absorption of new elements and technologies. Similarly, the conglomeration of manufacturers through mergers and acquisitions provides better access to the market and resources for modification of the offerings, as well as for innovations.
 

Primary stakeholders within the AI in asset management market focus on implementing AI-based analytics solutions to improve portfolio management and risk evaluation. They utilize predictive modelling through machine learning, automate investment processes, and enhance decision-making. Companies focus on AI-driven robo-advisors, and real-time market and sentiment analysis for better asset allocations. Collaboration with fintech and cloud companies strengthens AI capabilities.
 

AI in Asset Management Industry News

• In February 2025, Vital Voices Global Partnership, an NGO supporting women leaders across the globe, chose to implement Veritone Inc. AI-based Digital Media Hub (DMH) for better digital asset management and storytelling. The capital provided in this collaboration through Amazon Web Services (AWS) Marketplace is designed to support women’s changemakers through AI social good. It is currently employed by major brands such as NCAA, iHeartRadio, NBC Universal, CNBC, Bloomberg and CNN.
   
• In February 2025, Covet added an AI module to their platform that facilitates personal estate management, allowing users to manage their estate assets like never before. The platform uses AI technology to streamline the process of cataloging and appraising personal items such as jewelry, fine art, and collectables. This AI module provides market estimates and descriptions of the assets improving user understanding of intelligent decision making.
   
• Pacific Gas and Electric (PG&E) secured its existing collaboration with Sharper Shape by signing a 5-year contract for their CORE software’s utility asset management capabilities, further embedding the use of AI in utility asset management as of January 2025. The partnership enhances an existing one signed in 2019 and uses a sharpened version of remote asset management started by PG&E in 2021.
   
• Siemens Smart Infrastructure incorporated an AI-powered field service and asset management and grew its Siemens Xcelerator partner network, targeting the utility and heavy industry sectors that are plagued by poor infrastructure, supply chain, and human resource problems in July 2024. The solution contains monitoring that spots irregularities at the deepest floor level to enhance productivity by enabling ‘predictive’ maintenance instead of ‘break-fix’ maintenance.
   

The AI in asset management market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue ($ Mn/Bn) from 2021 to 2034, for the following segments:

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Market, By Technology

• Machine Learning (ML)
• Natural Language Processing (NLP)

Market, By Deployment Model

• On-premises
• Cloud-based

Market, By Application

• Portfolio optimization
• Conversational platform
• Risk & compliance
• Data analysis
• Process automation
• Others

Market, By End Use

• BFSI
• Retail and e-commerce
• Healthcare
• Energy and utilities
• Manufacturing
• Transportation & logistics
• Media & Entertainment
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Russia
  • Nordics
• Asia Pacific
  • China
  • Japan
  • India
  • South Korea
  • ANZ
  • Southeast Asia
• Latin America
  • Brazil
  • Mexico
  • Argentina
• MEA
  • UAE
  • Saudi Arabia
  • South Africa