Technology in financial advice has promised efficiency for years, yet many firms still find themselves buried in manual processes, duplicated data entry, and disconnected systems. Despite increasingly sophisticated tools, the underlying experience—both for advisors and clients—often remains fragmented.
In this conversation, Patrick Gardner and Aaron Breed explore a different way forward. Rather than focusing on individual tools, they centre the discussion around a single idea: clients should only have to tell their story once. From that starting point, the conversation unfolds into a deeper rethink of how advice businesses design their systems, workflows, and data architecture.
Most advice firms operate across multiple platforms—CRMs, onboarding tools, document systems, and communication channels. While each tool may serve its purpose, they rarely work together seamlessly. The result is a cycle of repetition: clients provide the same information multiple times, and teams continually re-enter or re-contextualise data across systems.
Over time, this creates more than just inefficiency. It erodes the client experience and introduces risk, as inconsistencies begin to appear between systems. What seems like a technology problem is, in reality, a design problem—one rooted in how systems are structured rather than what tools are used.
The idea that clients should only need to provide their information once sounds simple, but implementing it requires a fundamental shift in thinking. It moves the focus away from individual processes—such as onboarding or file notes—and toward building a shared context across the entire business.
In practice, this means that once client data is captured, it should flow naturally into every part of the advice process. Whether it is used for strategy development, documentation, or client communication, the same underlying information should remain consistent and accessible.
This approach reframes technology from a collection of tools into a connected system—one where data is not repeatedly handled, but continuously reused.
A recurring theme throughout the discussion is the importance of getting the fundamentals right before layering on complexity.
Before automation, before AI, and before advanced integrations, firms must first ensure their data is clean and structured. Without this, even the most sophisticated tools will struggle to deliver meaningful outcomes. As Breed explains, much of their early effort was spent organising and validating data—essentially “cleaning the house” before building anything new.
This highlights a common mistake in advice technology: adopting new tools in the hope they will fix underlying issues, rather than addressing those issues at the source.
While CRMs remain central to advice businesses, the way they are used is beginning to change. Instead of acting as the primary interface for all activity, they are increasingly becoming a system of record—a place where structured data lives, rather than where all work is performed.
Around this core, a more flexible architecture can be built. By using integrations and APIs, firms can connect multiple tools without being locked into a single ecosystem. This allows different components of the tech stack to evolve independently, while still maintaining a unified data structure.
The shift is subtle but important. It moves firms away from dependency on one platform and toward a more adaptable, modular approach.
One of the clearest examples of this new thinking is onboarding.
Traditionally, onboarding tools sit outside the core system, collecting data that must then be manually transferred into the CRM. This not only creates duplication but also introduces potential errors and inconsistencies.
By redesigning onboarding as part of a connected system, data can flow directly into the CRM and immediately become usable across workflows. This transforms onboarding from a standalone task into the first step in a continuous data journey—one that supports the entire client lifecycle.
Just as importantly, it improves the client experience. When forms are branded, intuitive, and integrated, they reflect the quality and professionalism of the advice being delivered.
Beyond capturing data, the discussion also explores how that data can be better used.
One example is the creation of visual entity maps—diagrams that illustrate relationships between individuals, companies, and trusts. Traditionally, these have been manual, time-consuming, and often difficult for clients to interpret.
By linking these visualisations directly to CRM data, they can be generated dynamically and updated automatically. This not only saves time but also enhances understanding, turning complex structures into something clients can easily grasp.
It is a small example of a broader idea: when systems are connected properly, data becomes more than just information—it becomes a tool for communication.
Artificial intelligence features prominently in the conversation, but not in the way it is often discussed.
Rather than focusing on AI as a standalone solution, the emphasis is on how it interacts with existing systems. The key insight is that AI is only as effective as the context it is given. Without structured, centralised data, its outputs are limited or inconsistent.
When integrated into a well-designed system, however, AI becomes far more powerful. It can assist with interpreting data, generating insights, and even visualising strategies in real time. But its effectiveness depends entirely on the quality and accessibility of the underlying information.
In this sense, AI does not replace the need for good systems—it amplifies their value.
Another important theme is the role of speed in innovation.
Rather than aiming for perfect solutions from the outset, the approach described is to build quickly, test ideas, and refine them based on feedback. This allows firms to validate concepts early and avoid investing heavily in solutions that may not work.
This iterative mindset lowers the barrier to innovation. Instead of requiring large budgets or long development cycles, firms can experiment with smaller ideas and scale what works.
It also reflects a broader shift in technology development—one where adaptability is more valuable than perfection.
Historically, many firms have relied on internal “tech champions”—individuals with the skills and interest to build and maintain systems. While effective in some cases, this approach is difficult to scale.
The conversation highlights a move toward systems that are more accessible and easier to implement. The goal is not to eliminate technical expertise, but to reduce the extent to which it is required for everyday operations.
By simplifying architecture and improving integration, firms can adopt more advanced technology without needing dedicated internal specialists.
Looking ahead, the direction is clear. Advice technology is moving toward greater flexibility, where firms are no longer tied to single platforms or rigid systems.
Instead, they can build modular tech stacks—selecting tools based on their specific needs and connecting them through shared data structures. This creates a more resilient and adaptable environment, one that can evolve alongside the business.
At the same time, the focus remains on the client. Technology is not being developed for its own sake, but to improve the experience of advice—making it more consistent, more efficient, and more personalised.
The conversation ultimately reflects a broader shift in how advice firms think about technology.
Rather than asking which tools to use, the more important question is how those tools work together. By focusing on data, context, and interoperability, firms can move beyond fragmented systems and toward a more cohesive model.
The idea of “tell your story once” captures this shift in a simple but powerful way. It is not just about efficiency—it is about respecting the client’s time, reducing friction, and building systems that support better advice.
In the end, the future of advice technology will not be defined by individual tools, but by how well those tools are connected.