Artificial intelligence is moving deeper into the global asset and wealth management industry, with major investment firms deploying AI for portfolio analysis, investment research, personalised advice, risk management and operational automation.
A U.S. News review highlighted seven major investment firms — BlackRock, JPMorgan Chase, Morgan Stanley, Vanguard, Goldman Sachs, Fidelity Investments and Wealthfront — that have incorporated AI into different parts of their investment and wealth management operations.
The trend reflects a broader shift in financial services from experimental AI applications towards tools that directly support investment professionals, financial advisers and clients. According to data cited from Nvidia’s 2025 State of AI in Financial Services report, around 70% of financial institutions surveyed reported AI-related revenue increases of at least 5%, while 60% reported operational cost reductions of 5% or more.
BlackRock has been one of the industry’s most prominent adopters of technology-driven investment management. Its Aladdin platform combines portfolio management, analytics and risk-management capabilities and is used both internally and by external institutions.
BlackRock has also developed Asimov, an AI-powered research platform functioning as a virtual investment analyst. The system scans research reports, company filings and internal information to produce insights for investment teams. The firm managed approximately $12.5 trillion in assets in mid-2025, illustrating the scale at which AI-enabled investment technology can potentially operate.
JPMorgan Chase
JPMorgan Chase has invested extensively in artificial intelligence across investment management and other financial operations.
Its AI tools include the LLM Suite, which provides employees with generative AI capabilities for information analysis and workflow automation, and PRBuddy, which assists with software code reviews.
Another established application, COIN — Contract Intelligence — uses technology to analyse commercial loan agreements and other documents. The system has been reported to process approximately 12,000 contracts annually, saving an estimated 360,000 hours of manual legal review work.
The bank is also applying AI to personalised portfolio construction and investment recommendations.
Morgan Stanley
Morgan Stanley has focused heavily on using generative AI to support its financial advisers.
Its AI @ Morgan Stanley Assistant gives advisers rapid access to the firm’s internal research and knowledge resources, while its Debrief application can generate meeting notes, identify key discussion points and help prepare follow-up actions.
The firm’s AI knowledge platform covers around 100,000 documents, and by mid-2024 it had reportedly been adopted by nearly all of Morgan Stanley’s approximately 20,000 financial-adviser teams. (Smart Money Mindset)
AI is therefore increasingly being positioned as an adviser-support system rather than a replacement for human investment professionals.
Vanguard
Vanguard is applying machine learning and AI to portfolio management, retirement planning and client communication.
Its digital advisory capabilities can construct personalised retirement portfolios using Vanguard investment products, while machine-learning techniques are also being applied within certain actively managed equity strategies.
In May 2025, Vanguard introduced a client-facing generative AI capability that provides investment advisers with personalised content based on factors such as a client’s financial knowledge, life stage and preferences. The company has also collaborated with the University of Toronto on AI research initiatives. (Smart Money Mindset)
Goldman Sachs
Goldman Sachs is integrating AI into investment banking and asset management activities, particularly in areas such as data analysis, financial modelling, risk assessment, compliance and operational automation.
Generative AI platforms can perform tasks that previously required considerable manual processing by junior professionals, enabling investment teams to dedicate more time to judgement-intensive analysis and strategic decisions.
Fidelity Investments
Fidelity is using AI to strengthen personalised investment services, portfolio analysis and customer support.
Its applications include automated investment-assessment tools, AI-assisted customer interactions and technology designed to help identify relevant investment opportunities based on investor characteristics and financial objectives. (Smart Money Mindset)
Wealthfront
Digital wealth manager Wealthfront represents a different model of AI-enabled asset management.
The platform uses automation and machine-learning capabilities for services including financial planning, portfolio construction, tax optimisation and automatic portfolio rebalancing, giving investors access to technology-driven portfolio management without relying exclusively on traditional adviser-led models. (Smart Money Mindset)
AI Reshaping the Investment Management Model
The growing adoption of AI indicates that its role in asset management is expanding beyond basic automation.
Investment firms are increasingly using AI to process large volumes of structured and unstructured information, detect investment patterns, personalise portfolios, improve adviser productivity and strengthen risk management.
Deloitte has also found that investment managers are expanding their AI capabilities across areas including customised portfolio recommendations, distribution and alternative-data analysis. About 60% of surveyed investment management firms were already using AI to some degree in data-related distribution activities, although only 11% characterised their usage as heavy.
However, wider adoption also introduces important governance issues. Investment firms must address data security, model validation, explainability, regulatory compliance, cybersecurity and human oversight as AI becomes increasingly embedded in investment decisions.
The emerging industry model is therefore likely to involve collaboration between technology and investment professionals, with AI providing faster analysis and deeper data processing while portfolio managers and advisers retain responsibility for judgement, accountability and client outcomes.
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