If evolution is a sign of a healthy ecosystem, the wealth management industry is exceedingly robust. Its ability to pivot in the face of consolidation, volatile markets, an impending shortage of advisors, accelerating demand for advice and disruptive technological innovation, all are signs of the industry’s resiliency. Foremost among wealth management’s challenges: the transformation of AI-driven service and support, from differentiators to table stakes in the space of a year.
As an industry that is aspirational at its core – financial advisors are in the possibilities business – wealth management is proficient at adapting to shifting landscapes in order to thrive. Recognizing the expectations of clients only matters if advisors are able to meet those expectations … and what clients want is personalized service. As little as a year ago, this would fly in the face of what firms are always looking to achieve: scale.
The advent of AI has made personalization at scale not only achievable, but assured, for those willing to embrace the new technology. But challenges remain:
- Regulators have not kept up with the pace of innovation. There is no comprehensive regulatory framework governing the use of AI in wealth management.
- People remain wary of the ultimate impact of AI on their portfolios and their lives. Explaining AI’s benefits – and the role it will play during the advisor/client lifecycle – to apprehensive clients requires skill and knowledge some advisors don’t yet possess.
- How can firms and advisors optimize AI and ensure accuracy when executing day-to-day administrative tasks?
The future of AI is exciting, and it’s now. Its application is both bold and nuanced, but its benefits are becoming clearer: Research shows early-adopter firms with a mature AI-driven operation have enjoyed 2.5% higher revenue growth than their lagging counterparts.
Maximizing the tool may be a trial and error proposition for many firms and integrating it into existing legacy platforms will be complex and expensive. A firm’s long-term success will be reliant and how quickly they get it right. To learn how industry participants are viewing the challenges and opportunities that accompany this AI revolution, we spoke to executives at three leading fintech providers to discuss what they are seeing on the front lines when it comes to AI in wealth management:
- John Messinger, Information Security Officer, FusionIQ, a leader in the delivery of cloud-based wealth management solutions
- Karl Roessner, CEO, Vestmark, a leading provider of portfolio management/trading solutions and outsourced services for financial institutions and their advisors
- Sindhu Joseph, CEO and Co-Founder, CogniCor, a provider of artificial intelligence enabled digital assistants and business automation platforms for the financial services industry
Specifically, we asked these questions of our experts:
- What are the challenges wealth management firms face when implementing AI before an established regulatory framework is in place?
- How should financial professionals be talking to clients about AI?
- What are proving to be the most effective uses of AI in a practice’s day-to-day?
Below are their insights.
John Messinger – The rapid evolution of AI in digital wealth management, driven by advancements in large language models, deep learning and natural language processing, presents both significant opportunities and complex challenges. These technologies, which automate routine tasks and provide deeper client insights, have the potential to transform advisory practices. However, the absence of a cohesive regulatory framework means firms must carefully navigate not only evolving guidance but also uncertainties around data privacy, suitability and client consent. To address this uncertainty, firms can responsibly leverage cutting-edge AI to streamline internal processes, such as risk management and compliance due diligence, while closely monitoring emerging standards. For instance, FusionIQ utilizes a proprietary large language model to enhance knowledge management across product and security documentation, enabling efficient information access and timely responses. By aligning AI initiatives with preliminary regulatory guidance and industry best practices, FusionIQ demonstrates how proactive planning can help firms adapt to a maturing regulatory landscape, ensuring that future rules will be met with minimal disruption.
Financial advisors should be excited about the innovation and rapid advancements in AI technology, viewing them as an opportunity to build trust, enhance transparency and create greater value in their client relationships. Advisors often face the challenge of balancing portfolio management, client interactions, compliance tasks and documentation while striving to grow their business. AI helps alleviate these pressures by offering deeper insights into client needs through advanced analytics, such as behavioral insights and accurate forecasting. FusionIQ is leading the way in integrating AI into wealth management with our cloud-native platform, offering capabilities like sentiment analysis, behavioral benchmarking, churn analysis and personalized relationship management. These tools empower advisors to better understand their clients, proactively identify new opportunities and strengthen relationships. Crucially, advisors should emphasize that AI is an enhancement, not a replacement, to their expertise – ensuring that the human insight and judgment clients value remain central to the advisory process. By leveraging AI, advisors can deliver tailored, data-driven recommendations that align with individual goals, personalize interactions and identify trends that elevate the wealth management experience.
AI is redefining the day-to-day practice of financial advisors by automating routine tasks, such as data entry and compliance documentation, allowing advisors to focus on building client relationships and delivering strategic insights. These efficiencies not only support growth and client satisfaction but also free advisors to invest more time in advanced quantitative analysis and market forecasting. Machine learning and large language models (LLMs) enhance an advisor’s ability to interpret complex data and provide personalized, goal-aligned recommendations, often leading to measurable improvements like faster response times, fewer administrative errors and higher client satisfaction scores. The adoption of AI must be accompanied by a steadfast commitment to data security and privacy. FusionIQ exemplifies how innovation can be balanced with responsibility, leveraging AI to refine client insights while implementing robust protections such as encryption and access controls. As regulatory guidance becomes more defined, advisors can look forward to even more nuanced AI applications, including predictive compliance monitoring and dynamic portfolio adjustments, ensuring that AI remains a trusted and transformative force in wealth management.
Karl Roessner –There is certainly fear of the unknown when using AI – particularly generative AI – especially in a highly regulated industry like wealth management. However, wealth management firms should realize that waiting around for regulatory guidance carries its own risks, especially if the guidance is likely to lean heavily on regulations around the usage of technology already in place. Challenges – or, in some cases, fears – around generative AI adoption typically revolve around two major concerns, which firms can mitigate today.
The first is accuracy: how do financial professionals trust the outputs generated by AI technology? We advise wealth management firms to keep their financial professionals as the “human in the loop,” checking the outputs and ultimately being responsible for whatever is generated.
The second challenge revolves around the sheer pace of change in AI. The number of applications being developed is staggering, and the capabilities of AI and large language models seem to grow by leaps and bounds almost every quarter. This keeps many firms on the sidelines waiting to see which capabilities and vendors will ultimately win out. But at this stage, it’s essential to get started, if only to learn what solutions will win out for you and your firm’s needs. This is also an area where your existing technology partners can – and should – be helping you identify where and how AI can be added to existing workflows within the applications your financial professionals are already using today.
There is a lot of talk about how AI will make advisors more efficient, which means advisors should talk about how they are going to use the time AI saves them to enhance their clients’ experience. Better than telling, show clients how they also benefit from AI adoption: for example, by sharing with a client the summarized meeting notes that a GenAI application created for the advisor.
Financial advisors should also be aware that their clients have likely asked GenAI chatbot questions that would be considered a solicitation for financial advice, even if only out of curiosity. Just as medical professionals often need to remind patients that “Google is not your doctor,” advisors should remind their clients “ChatGPT is not your financial advisor” – and then demonstrate how personalized knowledge of their family or life situation is critical to delivering the type of high-quality financial advice clients expect from their human advisors.
The earliest adoption of generative AI seems heavily focused on anything considered “text-based” work. Things like summarizing meeting notes or writing an email to a client are areas of day-to-day work that are immediately within the wheelhouse of large language models. This is not without risk or new areas of concern, particularly regarding data privacy and security (e.g., where the notes are stored, and the transfer of raw information to a large language model for processing).
An emerging area of interest – and one we think will explode in popularity in 2025 and beyond – is the addition of GenAI-driven “copilots” embedded in an advisor’s traditional software that can truly deliver on the incredible efficiency promises of AI. We imagine a world where instead of entering information and clicking through screens to generate a proposal or report, you ask your copilot to take on a task for you and deliver the result. But unlike humans, who can only execute so many tasks at a time, AI can operate at software-level scales, generating hundreds of proposals or thousands of performance reports all from a single request. This will not lead to AI replacing financial advisors, but it will see the start of AI-enabled financial advisors leveraging
Sindhu Joseph: In the absence of meaningful regulation of AI for wealth management firms, I have seen three main approaches to integration – each with unique challenges.
The first is highly conservative with firms choosing not to invest in AI solutions and integrations until regulations are in place. While this may prove the easiest option, there is no situation in which this is the right approach. AI-enabled advisors will triumph as they can take on more clients and provide more personalized service than advisors who aren’t adopting the technology. The reality is if you’re not moving forward, you are falling behind.
We also have seen a middle path in which firms take a small risk and implement AI-enabled solutions for well-tested use cases – such as note-taking and meeting preparation. I call this the FOMO (fear of missing out) approach. This approach provides some tactical advantages and more protection due to the high level of adoption across the industry. But it’s very much more reactive than strategic.
What we see as the best path is to create a strategic framework that allows AI-enabled solutions to work in tandem by streamlining disparate sources of records systems to create a unified, efficient and scalable system. This will allow advisors and firms to achieve scalable growth over the longer term. The approach requires thoughtful consideration of an AI partner with broad industry knowledge and awareness of potential regulations to mitigate the risk of a limited return on investment. At CogniCor, we are refining compliance processes to address response bias and provide traceability to regulators by providing source references and clear, logical explanations for the AI solution’s recommendation.
Time will tell what regulators will do, but we know that clients expect the kinds of efficiencies that only AI can deliver integrated into their advisor-client relationship. Discussing what AI can and cannot do – and what an advisor would not allow it to do – is critical. While AI can provide personalized advice, a financial advisor should be the one presenting it to the client.
Today’s technology can deliver so much more than the siloed solutions. A completely integrated AI solution – like CogniCor’s Wealth Co-Pilot – not only delivers the efficiencies people have come to expect but also enables advisors to deliver personalized service at scale. This will be critical as more advisors retire and demand for high-quality advice grows in the wake of the Great Wealth Transfer.
The wealth management industry deserves more than point solutions when technology can deliver so much more. Advisors and clients shouldn’t settle for less.
