Technology has always played a role in financial advice, but the current wave of AI-driven innovation represents something fundamentally different. It is not just improving efficiency at the margins—it is reshaping how advice is delivered, how businesses operate, and how decisions are made.
In this discussion with Peter Worn of Finura Group, the conversation moves beyond surface-level AI hype to explore what is actually changing within advice businesses. From practical use cases to strategic partnerships, the episode provides a grounded view of how technology is evolving—and where firms should be focusing their attention.
One of the clearest themes emerging from the discussion is the shift in how AI is being used.
Rather than simply automating tasks, AI is increasingly acting as a “thought partner.” Worn describes using AI to simulate a virtual board of directors—drawing on well-known business thinkers to help work through decisions and challenges. This reflects a broader shift: AI is not just executing instructions, but augmenting judgement.
In a business context, this extends into areas such as communication. For example, AI tools can analyse how an email might be interpreted before it is sent—helping advisors refine tone, clarity, and intent. These are small but meaningful improvements that compound over time.
While AI dominates much of the conversation, the foundation remains workflow efficiency—particularly in advice generation.
Advice Designer, one of Finura’s key products, was built to address a long-standing issue in the industry: the complexity and inefficiency of producing advice documents. Traditional systems rely heavily on templates and wizards, which are difficult to maintain and scale as requirements change.
The approach taken here is deliberately focused.
Rather than trying to do everything, the platform concentrates on one core function—generating high-quality advice documents and client-facing outputs. By pulling together data from multiple systems into a single interface, it simplifies what has historically been a fragmented process.
The impact of this focus is significant. For many firms, advice generation remains the primary bottleneck to growth, and improving this single area can unlock substantial capacity.
One of the more revealing insights from the conversation is how little visibility many firms have over their own processes.
The introduction of tools such as ROI calculators has highlighted the true cost of advice production—particularly the time spent by paraplanners and support staff. When measured over a year, these costs accumulate quickly, often justifying investment in better systems.
More broadly, this reflects a shift toward data-driven decision-making.
Rather than relying on anecdotal evidence, firms are beginning to track user behaviour, time spent, and workflow efficiency in a more structured way. This not only improves internal processes but also provides a clearer basis for future investment decisions.
Another key theme is the growing importance of integration.
As advice tech stacks become more complex, the ability for systems to work together seamlessly has become a primary consideration in software selection. In many cases, firms are prioritising integration over standalone functionality—recognising that even the best tool has limited value if it does not connect effectively with the rest of the ecosystem.
This is reflected in partnerships with platforms such as MyProsperity and Worksorted, where the focus is on creating a cohesive client and advisor experience rather than isolated solutions.
It also reinforces an important strategic principle: successful technology businesses do not try to do everything—they focus on their core function and integrate with others.
While the opportunities presented by AI are substantial, the discussion highlights an equally important consideration—risk.
Financial advice is a highly regulated profession, and the use of AI introduces new challenges around data security, compliance, and client trust. Unlike other industries, advice firms are dealing with sensitive client data, and mistakes can have significant consequences.
As a result, Worn emphasises the need for a measured approach.
Firms must adopt AI thoughtfully—ensuring they are not left behind, but also avoiding overenthusiastic implementation that could create new risks. This balance is critical, particularly in an environment where adoption is occurring at unprecedented speed.
For many firms, the challenge is not whether to adopt AI, but how much is enough.
Interestingly, the answer is not complex.
According to Worn, firms that are ahead are not necessarily those using the most advanced tools, but those that are embedding AI effectively into their existing workflows. This often starts with platforms such as Microsoft Copilot—leveraging integrated tools rather than layering on multiple standalone solutions.
Equally important is change management.
A significant portion of AI implementation is not technical, but organisational—training staff, adapting processes, and building confidence in new tools. Firms that can do this effectively are more likely to realise the benefits of AI than those chasing the latest innovation.
Looking ahead, one of the most significant developments is the rise of AI agents.
These are not standalone tools, but embedded capabilities that can operate within existing applications—handling tasks, responding to inputs, and supporting workflows in real time. Importantly, their value lies in integration, appearing within tools such as email, documents, and CRM systems rather than requiring separate interfaces.
However, this also introduces complexity.
As AI becomes more embedded, managing security, governance, and usage policies becomes increasingly important. The conversation highlights emerging concerns around both software and hardware—ranging from browser-based AI tools to recording devices that capture conversations automatically.
For advice firms, this represents a new frontier of risk management.
Despite the breadth of possibilities, the most effective applications of AI remain targeted.
Within Advice Designer, for example, AI is being explored in areas such as:
These use cases share a common characteristic—they enhance existing workflows rather than replacing them entirely.
This reinforces a broader point: AI is most valuable when applied to specific problems, not as a blanket solution.
The discussion also touches on the importance of partnerships in scaling technology.
The strategic investment by Hub24 into Advice Designer reflects a growing trend—where platform providers, technology firms, and advice businesses are becoming increasingly interconnected.
These partnerships are not just about capital.
They provide access to intellectual property, data, and capabilities that would be difficult to build independently. In a rapidly evolving environment, this can significantly accelerate development and innovation.
The evolution of advice technology is no longer theoretical—it is happening in real time.
AI is changing how decisions are made, how workflows are structured, and how advice is delivered. At the same time, it is introducing new challenges around governance, security, and implementation.
For advice firms, the path forward is not about adopting every new tool, but about building capability.
This means focusing on integration, embedding AI within existing workflows, and ensuring that people, processes, and technology evolve together. Firms that can achieve this balance will be well positioned to benefit from the next phase of innovation.
Ultimately, the future of financial advice will not be defined by technology alone—but by how effectively it is used to enhance the human elements of the profession.