The global AI in asset management market size was valued at USD 3.71 billion in 2023 and is expected to reach around USD 33.25 billion by 2033. The market is expanding at a solid CAGR of 24.52% from 2024 to 2033.
Key Points
- The North America AI in asset management market size reached USD 1.89 billion in 2023 and is expected to attain around USD 17.12 billion by 2033, poised to grow at a CAGR of 24.65% between 2024 and 2033.
- North America dominated the market with the largest revenue share of 51% in 2023.
- Asia Pacific is anticipated to showcase significant growth with the fastest CAGR in the market in the upcoming period.
- By technology, the machine learning segment has contributed more than 67% of revenue share in 2023.
- By technology, the NLP-natural language processing segment will grow at the fastest rate in the market over the forecast period.
- By application, the portfolio optimization segment has held a major revenue share of 28% in 2023.
- By application, the data analysis segment is predicted to witness prominent growth in the market over the forecasted period.
- By deployment mode, the on-premises segment has generated more than 56% of revenue share in 2023.
- By deployment mode, the cloud segment is anticipated to show the fastest growth in the market over the foreseeable period.
The AI in Asset Management market integrates artificial intelligence technologies to optimize the management of assets across various industries. It encompasses applications that use AI algorithms to analyze data, predict asset performance, and enhance decision-making processes for asset allocation and maintenance.
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Growth Factors
The growth of AI in Asset Management is driven by increasing demand for predictive analytics, automation of asset monitoring, and the need for efficient asset utilization. Advancements in machine learning algorithms and big data analytics further propel market expansion, enabling organizations to improve operational efficiency and reduce downtime.
In the AI in Asset Management market, several trends are shaping its evolution:
- Advanced Analytics and Predictive Maintenance: AI is being leveraged for advanced analytics to predict asset failures and optimize maintenance schedules, reducing downtime and operational costs.
- Automation of Asset Management Processes: AI-driven automation is streamlining asset tracking, monitoring, and management processes, improving efficiency and accuracy in asset lifecycle management.
- Integration with IoT and Edge Computing: AI is increasingly integrated with IoT devices and edge computing platforms to gather real-time data from assets, enabling proactive decision-making and enhancing operational visibility.
- Enhanced Risk Management: AI algorithms are enhancing risk assessment models by analyzing historical data and real-time market conditions, helping asset managers make informed decisions and mitigate risks effectively.
- Personalized Investment Strategies: AI-powered algorithms are offering personalized investment strategies based on individual investor profiles, risk tolerance, and market conditions, improving client engagement and satisfaction.
Region Insights
North America leads the AI in Asset Management market due to early adoption of AI technologies, presence of key industry players, and significant investments in digital transformation initiatives. Europe follows, characterized by strong regulatory frameworks promoting digitalization in asset management practices.
AI in Asset Management Market Scope
| Report Coverage | Details |
| Market Size by 2033 | USD 33.25 Billion |
| Market Size in 2023 | USD 3.71 Billion |
| Market Size in 2024 | USD 4.62 Billion |
| Market Growth Rate from 2024 to 2033 | CAGR of 24.52% |
| Largest Market | North America |
| Base Year | 2023 |
| Forecast Period | 2024 to 2033 |
| Segments Covered | Technology, Deployment Mode, Application, and Regions |
| Regions Covered | North America, Europe, Asia-Pacific, Latin America, and Middle East & Africa |
AI in Asset Management Market Dynamics
Drivers
Key drivers include the growing complexity of asset management tasks, rising need for real-time insights into asset performance, and the shift towards proactive maintenance strategies. AI’s ability to handle large datasets and provide actionable insights drives adoption across industries like manufacturing, energy, and transportation.
Opportunities
Opportunities lie in leveraging AI for predictive maintenance, optimizing asset lifecycle management, and enhancing asset performance through predictive analytics. Emerging economies present untapped potential for AI adoption in asset-intensive sectors, offering opportunities for market expansion and innovation.
Challenges
Challenges include data privacy concerns, integration complexities with existing systems, and the need for skilled AI talent. Resistance to change and high initial investment costs also pose challenges to widespread adoption of AI in Asset Management.
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AI in Asset Management Market Companies
- Amazon Web Services, Inc.
- BlackRock, Inc.
- CapitalG
- Charles Schwab & Co., Inc
- Genpact
- Infosys Limited
- International Business Machines Corporation
- IPsoft Inc.
- Lexalytics
- Microsoft
- TABLEAU SOFTWARE, LLC
- Next IT Corp.
- S&P Global
- Salesforce, Inc.
Recent Developments
- In February 2023, Arcadis, a leading organization for natural and built assets, started a collaboration with digital technology provider Niricson. Niricson works in using robotics, computer vision, and acoustic technology combined with AI to provide predictive asset management and condition assessments for bridges and other concrete infrastructure.
- In March 2022, Energy technology company Baker Hughes collaborated with C3 AI, Accenture, and Microsoft on industrial asset management (IAM) solutions for clients in the energy and industrial sectors. This collaboration improves the safety, efficiency, and emissions profile of industrial machines, field equipment, and other assets.
Segments Covered in the Report
By Technology
- Machine Learning
- Natural Language Processing (NLP)
- Others
By Deployment Mode
- On-premises
- Cloud
By Application
- Portfolio Optimization
- Conversational Platform
- Risk & Compliance
- Data Analysis
- Process Automation
- Others
By Geography
- North America
- Asia Pacific
- Europe
- Latin America
- Middle East & Africa
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