In recent years, a growing number of asset management firms have invested considerable sums in building out their artificial intelligence capabilities as the public at large agree that these tools should produce significant benefits to institutional investors. Unfortunately, this trend has prompted many asset managers to overstate the use of AI in their investment processes – a development that has created a variety of risks for both investors and the asset management firms themselves.
The Rise of AI Use in Asset Management
In the past few years, AI has become a cornerstone of innovation in asset management, with applications ranging from predictive analytics and portfolio optimization to client engagement and operational efficiency. According to a 2024 survey by Mercer, asset managers see significant opportunities in AI-driven value creation, particularly in equities, hedge funds, and digital assets.
The cost of AI used in the global asset management industry was valued at $3.4 billion in 2024 and is projected to grow to $21.7 billion by 2034, driven by the ability of AI to process vast datasets in real-time and deliver actionable insights. Firms like BlackRock have emphasized enhancing AI capabilities to automate processes and improve data handling, underscoring the technology’s transformative potential.
However, the enthusiasm for AI has led some firms to overstate their capabilities, giving rise to the issue termed “AI washing”. This practice mirrors earlier trends like “greenwashing” in ESG investing, where firms exaggerated their environmental credentials. AI washing involves making false or misleading claims about the extent or effectiveness of AI in investment strategies, often to lure investors seeking cutting-edge solutions.
Regulatory Scrutiny and Enforcement Actions
In recent years, regulators have intensified their focus on AI washing, particularly in the United States. In March 2024, the U.S. Securities and Exchange Commission (SEC) charged two investment advisers, Delphia (USA), Inc. and Global Predictions Inc., with AI-related violations, imposing $400,000 in penalties for misleading claims about their AI capabilities. The SEC’s actions highlighted concerns about “AI washing,” where these firms misrepresented the role of AI in their investment processes to attract investors.
The SEC’s “Operation AI Comply” in 2025 further underscored this crackdown, settling five cases related to AI washing and signaling a broader regulatory push to address deceptive marketing practices. The SEC’s July 2023 proposal to address conflicts of interest in AI-driven investment predictions has also set the stage for stricter oversight, with regulators seeking detailed information on firms’ AI models, training processes, and compliance frameworks.
Implications for Investor Trust
AI washing undermines investor confidence, a critical asset in an industry already grappling with fee compression and shifting preferences toward passive funds. In 2024, 70% of global mutual fund and ETF net flows went to passive products, reflecting investor demand for transparency and low-cost options. Misleading claims about asset managers’ AI capabilities can erode trust, especially when promised returns or efficiencies fail to materialize. For example, incorrect AI inputs or poorly designed algorithms can lead to erroneous investment decisions, resulting in financial losses and potential legal claims.
Moreover, AI washing risks creating a perception that firms prioritize marketing over substance. A 2024 BCG survey found that while 72% of asset managers believe generative AI will have a transformative impact, only 16% have a fully defined strategy for its implementation. This gap between expectation and execution fuels skepticism about the authenticity of AI-driven claims, further complicating efforts to build long-term client relationships.
Operational and Ethical Challenges
Beyond regulatory and trust issues, AI washing poses operational and ethical challenges. Firms that overstate their AI capabilities may lack the infrastructure to deliver on their promises, leading to inefficiencies and errors. Data quality and availability remain significant barriers, with many managers citing challenges in integrating AI with legacy systems. Poor data governance can result in biased or inaccurate outputs, exacerbating risks in portfolio management and trade execution.
Ethically, AI washing raises questions about accountability. Firms must ensure that AI models do not infringe on intellectual property or rely on unverified data sources, which could lead to legal disputes. Additionally, the lack of standardized regulations for AI use in finance creates uncertainty, with firms navigating a fragmented landscape of domestic and international rules.
Our Take
The global asset management industry, overseeing a record-breaking $128 trillion in assets under management (AUM) in 2024, has been navigating a transformative period marked by technological advancements, shifting investor preferences, and increasing regulatory scrutiny. Among the most significant developments is the rise of “AI washing,” a term describing the practice of exaggerating or misrepresenting the use of artificial intelligence (AI) in investment processes to attract investors and gain a competitive edge. In recent years, AI washing has emerged as a critical issue, raising concerns about transparency, regulatory compliance, and investor trust.
To address AI washing, asset managers must prioritize transparency and robust governance. Implementing clear AI strategies, as recommended by BCG’s three-step transformation framework, can help firms align their capabilities with client expectations. This includes investing in data quality, upskilling talent, and establishing ethical guidelines for AI use. Regulators, meanwhile, should continue to refine frameworks to prevent deceptive practices while fostering innovation.
The global asset management industry stands at a critical juncture. While AI offers immense potential to enhance productivity and personalize portfolios, the risks of AI washing threaten to undermine these benefits. By addressing these challenges head-on, firms can harness AI responsibly, ensuring sustainable growth and maintaining investor trust in an increasingly competitive landscape.
For more news about alternative data, investment research, and investment related FinTech, click here to sign up for our free ResearchWatch Weekly newsletter, or click here to subscribe to our proprietary ResearchWatch news and commentary service.