As AI continues to affect modern finance, including wealth management and private banking, we carry this article from one of the newer players in the field: Arta Finance.

We carry the following article from Caesar Sengupta (pictured, with more on the author, below), CEO, Arta Finance, a digitally-driven wealth management firm about which we have written before (such as here and here). Understandably, Sengupta is enthusiastic – within certain bounds – about the use of AI in wealth management. The sector continues to explore use cases for AI, and how this will hopefully improve the quality of services that flesh-and-blood clients receive. As with new technologies, there can be hype, concerns about costs, and the impact on wider business and society. 

The editors are pleased to share such commentaries; the usual editorial disclaimers apply to views of outside contributors. Remember, these articles are designed to foster conversations, so please get involved. Email tom.burroughes@wealthbriefing.com and amanda.cheesley@clearviewpublishing.com
 
Artificial intelligence is reshaping nearly every facet of the financial world, but perhaps no sector is being transformed as profoundly as wealth management. What was once a domain of exclusivity, reserved for high net worth individuals and accessible only through elite private banks or expensive financial advisors, is rapidly opening. AI is lowering the barriers to entry, making sophisticated investment tools and personalised financial planning available to a much broader audience.

The change is technological, philosophical and generational. Traditionally, wealth management was relationship-driven and labour-intensive. Advisors manually assessed portfolios, researched market trends, and created bespoke plans for each client. That model is effective but inherently limited – by time, cost, and access. 

AI shifts the equation. With intelligent systems capable of real-time analysis, behavioural personalisation, and natural language interaction, financial advice can now be scaled like software, offering tailored insights to millions, not just thousands. 

This ability to scale without sacrificing personalisation marks a profound shift. Historically, investors faced a trade-off: traditional advisory offered bespoke guidance, but only for the few who could afford it. Digital platforms expanded access, but delivered standardised, inflexible solutions. AI enables both –accessibility and bespoke experiences – at once.

The implications are enormous. Platforms across the financial services industry are beginning to roll out AI-powered tools that enhance both advisor productivity and client experience. Robinhood, for instance, has announced plans to offer AI-driven financial advice to its users, signalling a move beyond simple trading into full-service financial planning. Morgan Stanley is deploying an AI assistant that helps wealth advisors draft meeting notes and summarise client conversations, freeing them to focus more on relationship-building and strategic thinking. In Australia, Colonial First State is using Microsoft’s AI tool Copilot to help financial planners navigate complex regulations, significantly reducing the time it takes to deliver quality advice.

What all of these developments point to is a new paradigm: wealth management that is more efficient, more personalised, and crucially, more accessible. AI systems can now assess an individual’s goals, risk appetite, and financial history in seconds, generating personalised portfolio insights that might have taken a human advisor hours to prepare. These systems can continuously monitor markets, re-balance portfolios, and even simulate financial scenarios, acting like 24/7 digital advisors.

This evolution also has broader social and economic implications. For decades, institutional-grade financial tools and advice were effectively gated behind high minimum balances or expensive fees. AI is breaking that gate wide open. A new investor with $1,000 and a smartphone can now access guidance that mirrors what the ultra-wealthy might receive, not because the cost of advice has dropped, but because AI makes it scalable. In this sense, AI isn’t just optimising wealth management, it’s democratising it.

At the very frontier of what is possible currently, there is a broader shift towards AI-guided financial services – where clients can speak or type naturally, asking questions like, “How did my portfolio perform last month?” or “How should my portfolio change? I'm going to start paying for college tuition soon,” and receive clear, data-driven answers in real time, bringing together conversational ease with institutional-grade analysis.

Of course, innovation on this scale brings challenges. Data privacy is a top concern, especially when sensitive financial and personal information is involved. Regulatory compliance is another: ensuring that AI-driven insights meet fiduciary standards and does not mislead or misrepresent. Trust and transparency also matter as clients need to understand how AI models arrive at outputs and where the boundaries of automation lie. No one wants a black box managing their retirement fund without oversight.

But these challenges are not insurmountable. Leading institutions are already embedding AI ethics, explainability, and compliance into their systems. As the technology matures, hybrid models – combining human advisors with AI – are likely to become the norm. Advisors will focus more on strategic counsel and life planning, while AI handles the technical, analytical, and operational heavy lifting.

We’re witnessing a once-in-a-generation change in how people build, manage, and think about wealth. The firms that embrace this, not just by adding AI tools, but by rethinking their business models around accessibility and intelligence, will shape the future of finance. Wealth management is no longer a luxury service. Thanks to AI, it’s becoming a utility and one that everyone can access, understand, and benefit from.

About the author

Caesar Sengupta

Caesar Sengupta is co-founder and global CEO, Arta Finance. Sengupta has a passion for using technology to bring access around financial services. In his last role at Google as VP & GM of Payments & the Next Billion Users initiative, he led Google Pay, which went from none to more than 175 million users in about five years. He previously worked as an engineer at Encentuate and HP Labs. He holds 15 patents in operating systems design and expert finding systems and earned an MBA from the Wharton School and an MS in Computer Science from Stanford University. Sengupta resides in Singapore.