In wealth management, the firms that win aren’t always the ones with the best returns. Helping clients navigate complexity with clarity has become a competitive advantage, and artificial intelligence has become one of the most effective tools to maintain that edge. From portfolio optimization to tax-aware planning, AI is helping advisors scale personalized insights, manage risk, and deliver better experiences in less time.
This shift is already underway. Morgan Stanley’s AI-powered assistant is streamlining research for thousands of financial advisors. JPMorgan Chase has launched IndexGPT, its generative AI model for investment selection. EY reports that nearly all wealth managers are piloting AI, with many anticipating that it will be central to their strategy.
AI isn’t replacing the advisor; it’s enhancing the way we serve clients. And firms that lean in now are setting the standard for what modern wealth management looks like.
Fast, Personalized Insights: The AI Edge
In today’s market, speed and precision are table stakes. AI enables advisors to deliver both. Tools like JPMorgan’s Coach AI, which helped the firm’s wealth unit respond to April 2025 market swings, illustrate what’s possible when machine learning augments human judgment. According to JPMorgan, the tool enabled advisors to draft personalized client responses 95% faster, resulting in a 20% year-over-year increase in gross sales.
That kind of agility is becoming the norm. BlackRock’s Asimov platform processes portfolio risk in real-time, helping managers make informed decisions as markets evolve. These systems are built to assist, not replace, financial professionals. BNY Pershing CIO Michael Lewis cautions against blind trust in automation: “We often assume that when AI generates an answer, it must be right. And that's not true at all.” AI doesn’t make financial planning easier; it makes it smarter. But without context and critical thinking from the advisor, you’re just speeding up mistakes.”
Used responsibly, AI becomes a force multiplier, turning raw data into actionable intelligence and empowering advisors to be more present and strategic in their client relationships.
Streamlining Operations: AI Behind the Scenes
AI is also quietly revolutionizing how firms operate behind the curtain. Many of the most time-consuming and error-prone functions, such as document review, compliance checks, and data extraction, are now handled by AI-powered “digital workers.” At BNY Pershing, for instance, automated systems are already taking over repetitive technical processes, improving both speed and accuracy.
That’s freeing up advisors to do what only humans can: build trust, solve complex problems, and deliver long-term value. PwC predicts that AI-powered platforms will manage nearly $6 trillion in assets by 2027, nearly double 2022 levels. This growth is being driven not just by efficiency, but by the need to scale personalized service without scaling headcount.
According to EY, early use cases include trade execution, client onboarding, and marketing automation.⁶ While some firms are still hesitant, those that integrate AI holistically are already seeing improved engagement and operational resilience.
Cash flow, compliance, and onboarding are all part of the client experience. When those systems run smoothly, it’s not just about saving time. It’s about building credibility.
Navigating Risk: Why Governance Matters
AI may streamline decision-making and unlock client insights, but it also introduces new forms of risk, particularly in terms of data quality, regulatory oversight, and ethical transparency. As BNY Pershing CIO Michael Lewis says, “We often assume that when AI generates an answer, it must be right. And that’s not true at all.”
Recent data backs this up. A 2023 EY-Parthenon survey found that only 61% of wealth managers have a formal governance framework for managing external AI data, highlighting widespread gaps in privacy, bias monitoring, and model accountability. Meanwhile, both the SEC and CFTC have made it clear that financial firms are now expected to validate AI model outputs, disclose the sources of training data, and maintain audit-ready controls.
AI without governance is like giving a calculator to someone who never learned math. It might give you a fast answer, but you won’t know if it’s the right one. True value lies in pairing automation with a clear-eyed strategy that accounts for data integrity, compliance, and decision accountability.
Operational Playbook for Advisors
If you're advising clients in today’s AI-powered landscape, here’s how to build confidence and reduce risk:
Augment, don’t replace: Use AI for tasks like research, segmentation, and modeling—but keep humans in the loop. As Dan notes, “AI gives you the draft, but the advisor delivers the strategy.”
Establish a governance plan: Document your model inputs, data sources, and decision logic. Regulators now expect this level of clarity.
Upskill across the board: With 80% of firms planning AI-led transformation by 2028 (PwC, TIME), AI fluency is becoming as important as financial modeling. Advisors who understand AI’s strengths—and limits—will lead the next chapter.
Pilot, don’t overbuild: BNY Pershing’s AI strategy started with targeted tools for client onboarding and compliance before scaling. This staged approach reduces risk and builds internal buy-in.
Conclusion
AI is reshaping the wealth management experience—boosting speed, accuracy, and personalization. But progress depends on pairing tech adoption with sound judgment and strong governance. As PwC reports, 80% of firms expect AI to increase revenue, especially through self-service tools and automated analysis (PwC).
For advisors, this isn’t about replacing what works; it’s about evolving how we work. By designing operations around both efficiency and oversight, firms can deliver the confidence clients demand and unlock new levels of service, strategy, and scale.
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