The relationship between financial advisors and their technology has always been defined by dependence. Advisors evaluated platforms, selected tools, and then conformed their workflows to what those systems allowed. Platforms essentially said, “You’ll use what we give you, and you’ll like it!”
That dynamic is now shifting as generative and agentic AI have moved exponentially this past year from experimental capability to embedded infrastructure.
Advisors are no longer just users of technology. They are increasingly acting as builders.
This shift begins with access. Generative AI lowers the technical barrier that once separated the idea from execution. Advisors who understand their client base, their planning philosophy, and their operational gaps can now translate that knowledge into working tools. A prompt becomes a prototype. An automated workflow replaces a manual process. A custom client report can be generated on demand with logic that reflects the advisor’s own voice and priorities.
Agentic AI extends this further. It introduces systems that can take on tasks, coordinate across data sources, and iterate toward outcomes. The advisor isn’t writing code in the traditional sense, but the role begins to resemble that of a coder. They define objectives, structure instructions, and refine outputs in a continuous loop. In practice, that looks a lot like being a CTO.
This evolution changes the core expectations placed on advisors. Technical fluency is now part of the job description. Not fluency in programming languages, but fluency in systems thinking. Advisors need to understand how data flows, tools interact, and how to direct AI to produce consistent results. The skill set expands from selecting vendors to designing solutions. That’s a big shift.
For many firms, this will create a new layer of differentiation. Advisors who lean into this model can create highly tailored experiences that reflect the nuances of their client relationships. A planning tool can incorporate firm-specific assumptions. A communication workflow can reflect the cadence and tone that clients expect.
This has direct consequences for fintech companies. For years, fintech has operated on a model of aggregation. Build a comprehensive platform, add features over time, and capture advisors within a broader ecosystem. That model depends on scale and standardization. It assumes that most firms will accept a shared roadmap.
That assumption doesn’t work anymore, though. When advisors can build or modify their own tools, the value of a monolithic platform becomes less clear. Advisors may favor point-solution components that can be integrated and customized. They may prioritize access to data and interoperability rather than an expanded feature set. The center of gravity shifts from the product itself to the flexibility of the product.
Fintech firms will need to respond by rethinking their role. Instead of delivering complete solutions, they may need to provide frameworks. Instead of controlling the user experience end to end, they should support extension and modification. This involves opening APIs, enabling customization at a deeper level, and accepting that the final experience may look different across firms.
There is also a shift in pricing. When an advisor can replicate or mimic a feature with AI, the perceived value of that feature declines. Pricing will need to reflect, not just functionality, but the quality, reliability, and integration of that functionality within a broader system.
Meanwhile, there are new opportunities for wealthtech providers that understand this transition. Tools that help advisors orchestrate AI systems, manage data pipelines, and maintain governance will become more relevant. Infrastructure matters more than the interface. The companies that succeed will likely be those that empower advisors to build while ensuring consistency, compliance, and scalability.
The implications extend to end clients, too. A more technical advisor can deliver more personalization. Planning outputs can reflect real-time data. Communication can be tailored with a degree of precision that was difficult to achieve with standardized templates. Clients benefit from solutions that feel more aligned with their specific circumstances. (And, by the way, many clients are relying on AI to check their advisors’ work anyhow.)
But, like all things in life and finance, there’s a tradeoff. As advisors take on more responsibility for building and maintaining their own tools, they also assume more risk. The quality of outputs depends on how systems are configured. The consistency of advice depends on how workflows are defined. Governance, particularly on data, becomes a critical issue. Clients are placing trust not just in the advisor’s judgment, but in the systems the advisor has designed.
What is emerging is a more dynamic environment. Advisors aren’t replacing fintech, and fintech is not fading into the background. Instead, the boundary between the two is becoming more nebulous. Advisors are building, fintech firms are enabling, and clients are experiencing outcomes shaped by both.
The firms that succeed will be those that recognize this shift early. Advisors who invest in developing technical fluency will gain a level of control that was not previously available. Fintech companies that embrace flexibility over control will remain relevant as the market evolves.
Justin Whitehead is founder and CEO of Pebble Finance, a portfolio analytics and technology company that synthesizes news and proprietary research, connecting the dots between real-world events and investment performance.
This article originally appeared in Financial Advisor Magazine.
