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Artificial Intelligence (AI) in Asset Management Market Size Forecast: How Big Could The Market Get By 2030?
The market size for artificial intelligence (AI) in asset management has experienced substantial growth in recent years. This sector is expected to expand from $5.39 billion in 2025 to $7.1 billion in 2026, achieving a compound annual growth rate (CAGR) of 31.9%. Historically, this growth can be ascribed to several factors including the proliferation of digital asset management tools, the escalating complexity of investment portfolios, enhanced availability of financial data, the necessity for reducing errors in asset tracking, and the widespread adoption of analytics-driven decision making.
The artificial intelligence (AI) in asset management market size is anticipated to undergo significant growth over the next few years, projected to reach $21.82 billion by 2030, exhibiting a compound annual growth rate (CAGR) of 32.4%. This expansion during the forecast period is driven by several factors, including the increasing adoption of AI-powered financial platforms, a growing demand for real-time asset visibility, the advancement of algorithmic investment strategies, the integration of AI with blockchain-based assets, and the expansion of cloud-based asset management solutions. Prominent trends expected in this period involve automated asset tracking and monitoring, AI-driven portfolio optimization, predictive asset performance analytics, intelligent risk and compliance automation, and real-time investment decision support.
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Artificial Intelligence (AI) in Asset Management Market Growth Drivers: What’s Behind The Acceleration?
The increasing demand for advanced fraud detection methods is expected to propel the expansion of artificial intelligence (AI) within the asset management market going forward. Fraud detection specifically refers to the process of identifying and averting fraudulent activities or behaviors within a system or organization. The integration of AI in asset management for fraud detection provides efficiency, accuracy, early discovery of anomalies, real-time observation, enables the analysis of user conduct and transaction patterns, and adaptability to the dynamic landscape of financial security. For instance, in October 2024, according to the U.S. Department of the Treasury, a US-based government executive agency, its Office of Payment Integrity prevented and recovered over US$4 billion in fraud and improper payments during fiscal year 2024, which was an increase from US$652.7 million in fiscal year 2023, by employing enhanced fraud-detection processes, including machine-learning AI. Therefore, the growing necessity for sophisticated fraud detection solutions is driving the growth of AI in the asset-management market.
Artificial Intelligence (AI) in Asset Management Market Segment Landscape: Which Areas Lead Development?
The artificial intelligence (AI) in asset management market covered in this report is segmented –
1) By Technology: Machine Learning And Deep Learning, Natural Language Processing, Predictive Analytics
2) By Deployment: On-Premise, On-Cloud
3) By Application: Portfolio Optimization, Risk And Compliance, Process Automation, Conversational Platform, Data Analysis, Other Applications
4) By Industry Vertical: Banking, Financial Services, And Insurance (BFSI), Healthcare, Retail And E-Commerce, Media And Entertainment, Energy And Utilities, Automotive, Other Industry Verticals
Subsegments:
1) By Machine Learning And Deep Learning: Supervised Learning, Unsupervised Learning, Reinforcement Learning, Neural Networks
2) By Natural Language Processing (NLP): Sentiment Analysis, Text Analytics, Chatbots And Virtual Assistants, Language Translation
3) By Predictive Analytics: Time Series Forecasting, Risk Assessment Models, Portfolio Optimization, Market Trend Analysis
Artificial Intelligence (AI) in Asset Management Market Trends: What’s Defining The Industry’s Next Phase?
Leading companies in the **artificial intelligence (AI) in asset management market** are developing new products, such as next-generation AI supercomputing services, to secure a competitive advantage. An AI supercomputing service generally refers to a cloud-based or specialized computing offering that provides high-performance resources specifically optimized for AI workloads. For example, in **March 2023**, the US-based technology company, **NVIDIA Corporation**, released **DGX Cloud**. **DGX Cloud** is a service enabling businesses to gain immediate access to **NVIDIA AI supercomputing** in global cloud environments through a web browser. It operates as an AI-training-as-a-service platform, providing enterprise developers with a serverless environment tailored for generative AI. Through **DGX Cloud**, businesses can utilize their own AI supercomputer using a standard web browser. Each **DGX Cloud** instance is outfitted with **eight NVIDIA 80GB Tensor Core GPUs**, delivering **640GB of GPU memory** per instance.
Artificial Intelligence (AI) in Asset Management Market Industry Leaders And Competitive Landscape
Major companies operating in the artificial intelligence (AI) in asset management market are 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.
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Artificial Intelligence (AI) in Asset Management Market Regional Analysis And Top Geography
North America was the largest region in the artificial intelligence (AI) in asset management market in 2025. The regions covered in the artificial intelligence (AI) in asset management market report are Asia-Pacific, South East Asia, Western Europe, Eastern Europe, North America, South America, Middle East, Africa.
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Wasay has over a decade of experience in market research, data modelling, and analytics, with prior experience at GlobalData and Decision Tree Consulting Services. At The Business Research Company , he leads research operations across syndicated studies, customized consulting engagements, and the Global Market Model platform. His professional experience includes supporting organizations such as Boston Consulting Group, KPMG, and Ernst & Young. Wasay holds a degree in Electronics and Communications Engineering, postgraduate management qualifications from International Management Institute Belgium and Indian School of Business and Entrepreneurship, and completed the Integrated Program in Business Analytics from Indian Institute of Management Indore.
