The stuff of science fiction has catapulted from the big screen to the back, middle and front offices of enterprises across the business spectrum. While the hyperbole surrounding artificial intelligence (AI) has settled into an energized buzz, technological advancements continue apace. The iterative AI processes that continually refine, redeploy and optimize capabilities are driven by money, time, energy and human ingenuity. Everyone is betting on reaping the rewards of AI functionality with a seemingly limitless potential to do more, better, cheaper and faster than ever before. The potential may indeed be extraordinary. But unlocking it comes with impediments – both in terms of execution and adapting the technology to function within existing ecosystems.
Sindhu Joseph is CEO and Co-Founder of CogniCor, a provider of AI-enabled platforms for financial services firms. The company has been at the forefront of developing and delivering AI-driven solutions to wealth management firms keen on leveraging the technology’s transformative ability to redefine workflows, drive growth and build scale. Given her front-row seat to the AI innovation introduction to the industry, she notes, “For a generation, we have seen an almost religious devotion to the idea of disruption within the technology space. Disruptors operate outside of the system, which is useful in some cases but doesn’t work as well in an industry with a fragmented tech stack that delivers critical services. Point solutions, such as notetakers or meeting assistants, can enhance operations but do nothing to enable intelligent data utilization across this fragmented ecosystem.”
The wealth management industry, where CogniCor has been an active presence since its founding 2018, has already seen AI-driven efficiencies at work in compliance, data gathering and marketing functions. Visionaries – as well as bean counters – are looking toward its next evolution: agentic AI, a type of artificial intelligence that can make autonomous decisions and act independently to solve multi-step problems.
Many industry players hold a positive outlook on agentic AI’s role in financial services across multiple functions and with far-reaching implications. Sloan Shanahan, Chief Revenue Officer at FusionIQ, a cloud-based wealth management solutions provider, believes “agentic AI is a total game-changer for wealth tech firms, supercharging growth. By personalizing client interactions and investment recommendations, agentic AI builds stronger relationships and unlocks brand-new revenue streams. Specifically, it sharpens portfolio management, streamlines compliance and strategically deploys resources to the most promising initiatives.”
Everyone agrees it’s a big leap, with some in wealth management concerned that in working toward unlocking agentic AI’s full value, business executives are overestimating what that will actually look like in terms of practical, day-to-day functionality.
“Wealth management enterprises adopting agentic AI must navigate key data governance risks to ensure compliance, security, and trust,” notes Sid Yenamandra, Founder and CEO of Surge Ventures, a SaaS venture studio targeting the financial services and wealth management industries. Regulatory adherence (SEC, FINRA, GDPR) is critical, as improper data handling can lead to fines and legal exposure. AI models also risk inheriting biases from training data, potentially generating misleading financial insights, necessitating transparency and rigorous monitoring.”
Putting the agentic AI in RIA: A view from the field
RIAs big and small, particularly firms with an eye toward consolidation and aggregation, have a high bar when it comes to tech integration that increases as new firms join. This challenge of integrating new technologies with existing platforms is not new. But it’s a hurdle that may increase with agentic AI both in terms of functionality and cost.
Robert Coppola, CTO at Sanctuary Wealth, a platform supporting a network of 120 partner firms owned by independent advisors, says, “Implementing AI in wealth management can require significant upfront investment in terms of both time and money. Executives need to perform a thorough cost-benefit analysis to assess the long-term ROI, taking into account potential cost reductions and revenue enhancements.” He adds, “It’s not a one-time investment. Executives need to plan for ongoing maintenance, updates and the potential introduction of new models or algorithms to ensure the technology remains effective and competitive.”
Agentic AI’s potential to identify and deliver hyper-personalization at scale across diverse client bases is particularly important in a relationship-centric industry like wealth management. While financial advisors are expected to remain central to the business of advice, projections are calling for a 100,000 financial advisor shortfall by 2034 due to an aging and retiring advisor population. Add the large generational wealth transfer taking place and rising client expectations, and it’s a perfect storm that many believe can be quelled by AI. But that won’t just happen. Firms must invest wisely in the technology and understand how to get the most out of it.
Most industry insiders recognize this is easier said than done. “While technology can address several efficiency and scalability issues, too many firms are unwilling to leverage AI to its full potential,” said Greg Gessert, Chief Growth Officer at VestGen Wealth Partners. “The industry can, and should, invest in solutions to help address the changing dynamics of our advisor population and evolving client demands.” He adds that because his firm, which was founded in December 2024 to support succession-minded financial advisors and cultivate next-gen wealth industry leaders, doesn’t have the tech-related constraints of older firms – such as integrating legacy tech stacks – is an advantage that allowed his firm to put AI-driven solutions at the core of its business at the get-go.
People remain central to the success of agentic AI
What most industry participants agree on is the need for human capabilities to keep pace with technological advancements. Coppola believes that “wealth management firms need a combination of AI experts, data scientists and financial domain specialists to create tailored solutions.”
For RIAs of all sizes, how successful agentic AI is in building efficiencies and driving growth for stakeholders is where the rubber will meet the road. As Joseph put it, “AI should serve as an enabler, empowering an advisor or firm to modernize, streamline and enhance operations without overhauling systems.”
Security is a major concern, with Yenamandra noting, “AI-driven systems process vast amounts of sensitive data, making them prime targets for cyber threats. Firms must establish clear accountability measures, ensuring that AI-driven recommendations have human oversight, particularly in high-stakes decisions. Without proper safeguards, AI can introduce operational, ethical and compliance risks that undermine client trust.”
However, Gessert does see a potential impact on firm headcounts, saying, “It’s entirely possible that firms will not have the same staff requirements going forward as we apply agentic AI solutions within the industry. We are making these investments to future-proof our operations.”
Joseph concluded, “AI can serve as an enabler of seamless interaction among advisors, clients and workflows. Wealth management firms that want to continue growing in this changing market must leverage an AI-enabled middle office as part of a larger strategic vision to optimize and scale their business. Outlining tangible steps toward this goal and using the best tools to achieve them, including AI-enabled solutions, will be critical to future success.”
