Trends and applications of gen AI, blockchain in wealth management

The business of wealth management has long been designed for high-net-worth clients in the financial spectrum. Individuals with substantial financial resources can access dedicated financial advisors who provide personalized investment strategies and customized asset allocation plans.

These services are meticulously tailored to their unique financial circumstances, long-term objectives, and risk preferences. The solutions offered are comprehensive, detailed, and often involve complex instruments and diversified portfolios that align with their wealth preservation and growth goals.

In contrast, individuals who lack access to such exclusive services traditionally have to rely on their own judgment, limited knowledge, and publicly available information when making financial decisions. Without professional assistance or in-depth financial literacy, many individuals are left to navigate the complexities of investing, saving, and retirement planning on their own.

This disparity has widened the financial knowledge gap and led to unequal outcomes in wealth accumulation and financial security.

Digital Transformation: The Role of Gen AI and Blockchain

However, with the rapid and continuous advancement of generative artificial intelligence (Gen AI) and blockchain technology, this traditional wealth management model is undergoing significant change. The development of financial technology (FinTech) is reshaping how financial services are delivered and accessed, and it is moving at a pace that is faster than ever before.

Gen AI enables more timely, adaptive, and customized financial advice, while blockchain introduces a reliable and tamper-proof system for handling sensitive financial data. Together, these technologies are bringing about a structural shift in the industry, transitioning wealth management into a new phase defined by digital transformation and increased accessibility.

Accenture’s North American Wealth Management Advisor Survey revealed that 96% of respondents think Gen AI can revolutionize the way clients are served in investment management. Additionally, 97% of surveyed advisors foresee Gen AI’s most significant changes within the next three years.

This shift represents a meaningful turning point, as financial services are no longer limited to a select group of high-net-worth individuals. Instead, they are evolving into more inclusive and widely available digital tools, offering asset management solutions to a much broader and diverse population. The traditional boundaries that once defined who could access professional advice are being challenged and redefined by this technological progress.

Gen AI has introduced two of the most transformative changes in the wealth management landscape. The range of people who can benefit from these services has been greatly expanded and the overall efficiency and responsiveness of service delivery has been improved.

Robo-Advisors and AI-Driven Portfolio Management

Previously, financial advisory services were often cost-prohibitive and resource-intensive, requiring significant time and effort from human advisors. These limitations meant that only clients with sufficient assets could justify the costs of having these advisors.

Today, the integration of Gen AI has altered this dynamic by reducing costs and enhancing scalability. These improvements have made it feasible for general consumers, including beginners who are just starting to build their financial portfolio, to access sophisticated financial guidance.

Among the most widely adopted applications of Gen AI, Robo-advisors deliver the practical implementation of AI-powered automation in financial advisory. These applications can generate investment and asset allocation recommendations by analyzing user-specific inputs such as age, income, risk appetite, investment timeframe, and financial goals.

Robo-advisors can also automatically monitor and update portfolio allocations in real time, adapting to changes in financial markets, shifts in economic conditions, or updates in personal circumstances. The benefits of this level of automation include reduced reliance on manual intervention, increased speed in decision-making, and the ability to deliver consistent advice without emotional bias.

Gen AI can analyze historical market data to develop optimized portfolios. It helps wealth managers identify investment strategies by stimulating thousands of scenarios. This process can be fed back to Gen AI and improve the practices over and over.

This automation not only improves operational efficiency but also allows financial institutions to expand their client base significantly while keeping service quality high and costs manageable. In this way, AI lowers the barriers to receiving professional financial advice and supports the broader goal of enhancing financial inclusion, giving more people the opportunity to plan for their financial well-being.

Personalization, Marketing, and Risk Management

Gen AI is widely utilized across other critical functions in wealth management, such as precision marketing, customer profiling, and personalized product recommendations. Through the collection and analysis of large volumes of user data—including transactional records, browsing behavior, and digital interaction patterns—AI systems can develop detailed user profiles.

These profiles allow financial institutions to better understand client preferences and proactively suggest tailored financial products and services that closely match each individual’s needs and objectives. This personalized approach increases user engagement, improves conversion rates, and contributes to higher levels of satisfaction and loyalty.

Furthermore, Gen AI plays an essential role in strengthening institutional risk management capabilities. Through the use of advanced anomaly detection techniques, AI systems can continuously monitor user activities and identify irregular behaviors or suspicious transactions. The early detection of such anomalies enables timely intervention, helping institutions to prevent fraud, reduce exposure to financial loss, and protect customer assets with greater precision and responsiveness compared to traditional risk monitoring systems.

As Gen AI systems depend heavily on the quality, accuracy, and transparency of input data, blockchain technology has emerged as a critical infrastructure to support these systems. Blockchain is built upon three foundational characteristics—decentralization, immutability, and transparency—that collectively address the long-standing challenges of verifying data authenticity in financial environments. Within wealth management, blockchain can be used to securely record a wide range of sensitive data, including transaction histories, investment activity, asset transfers, credit information, and legal documentation related to loans or agreements.

Since the data stored on blockchain networks is encrypted and cannot be modified retroactively without broad consensus, it ensures a high standard of reliability and auditability. This makes it valuable for building trust in data sources that feed into AI systems.

For small and medium-sized enterprises (SMEs), blockchain applications in financing and credit analysis can help build accurate, up-to-date credit histories, which may otherwise be difficult to compile. By enhancing data integrity, blockchain helps bridge gaps in financial access and supports more equitable treatment in lending decisions.

Token-Based Economies and User Engagement


A related trend gaining momentum in this space is the emergence of token-based economies. On modern wealth management platforms, tokens are no longer limited to acting as tools of transaction. They are increasingly being used as incentives for user engagement.

For example, users who take part in investment learning modules, contribute feedback, or participate in beta-testing new digital services can be rewarded with platform-specific utility tokens. These tokens represent tangible rewards that encourage a cycle of engagement, contribution, and recognition.

This mechanism reflects an important evolution in platform structure. Rather than passive service providers, platforms are becoming active financial ecosystems that invite user participation and shared value creation.

The integration of Gen AI and blockchain is not just a technological combination, but a pathway toward innovation that transforms foundational processes. AI systems can leverage data stored on blockchain networks to make more accurate and explainable decisions.

Meanwhile, blockchain can record the logic, updates, and decision-making history of AI systems, creating an auditable trail of accountability. This transparency helps reduce reliance on opaque “black box” models and enables greater trust in AI-driven recommendations. In practice, this integration is already being piloted in areas such as cross-border investing, insurance claims automation, digital identity validation, and behavioral finance applications.

A lot of Fintech companies and startups are providing wealth management consultants more efficiently than traditional financial institutions. These companies provide market analyses and forecasts, hyper-personalization, and portfolio management to non-high-net-worth individuals with their niche skills and have become important market players in the wealth management business.

As adoption continues to grow, regulatory bodies around the world are becoming increasingly focused on governance frameworks for these technologies. Leading institutions such as the International Organization of Securities Commissions (IOSCO), the Bank for International Settlements (BIS), the European Union, and the Monetary Authority of Singapore (MAS) have introduced guidance to ensure that financial institutions applying AI adhere to principles of fairness, explainability, accountability, and data privacy.

In 2024, the European Union passed the Artificial Intelligence Act, which applies stricter oversight to high-risk AI applications in financial contexts. Similarly, regulations around blockchain and token-based systems are evolving quickly.

Countries are working on frameworks that address legal standards for cross-border capital movement, digital asset issuance, smart contract enforceability, and accountability in decentralized systems. Taiwan’s Financial Supervisory Commission (FSC) has introduced six key principles for AI governance, covering fairness, transparency, risk control, data integrity, accountability, and the preservation of human-centered values.

These frameworks reflect a growing effort to guide innovation while maintaining systemic stability and protecting consumer rights.

Challenges and Future Directions

Despite the promising potential of Gen AI and blockchain in wealth management, several challenges remain. These include data privacy concerns, ethical complexities, the difficulty of integrating diverse technological systems, and a general lack of mature, harmonized global regulations.

In a field as sensitive as wealth management—where personal assets, trust, and long-term financial goals are involved—technology must not only focus on efficiency but also prioritize transparency, accountability, and user-centric values.

Trust is the key to a successful advice relationship, but whether Gen AI can replace the trust people have in human advisors remains an open question.

The objective of innovations is not to replace people, but to extend their capabilities and reinforce trust between clients and service providers. Only within a framework of responsible AI and transparent blockchain governance can these technologies realize their full potential.

I suggest two critical points to investors. First, the trustees should deliver clear messaging about AI's role as a complementary tool and provide human interactions. Second, the investors’ financial literacy should continuously be strengthened for better investment judgment. After all, communication fails if investors do not comprehend the information.