For decades, financial advice has been constrained by one persistent reality: inefficiency. Despite advances in technology, many core workflows—particularly the production of Statements of Advice (SOAs)—have remained largely unchanged. Tasks that took hours or even days years ago continue to demand similar effort today, creating bottlenecks that limit both advisor productivity and client access to advice.
In a conversation between Patrick Gardner and Steven Goh, co-founder of Fable, this challenge is addressed directly. Rather than incremental improvements, Fable represents a more fundamental shift—one that reimagines how financial advice work is completed through agentic AI systems.
What emerges is not a story about automation replacing humans, but about transforming the way advisors work—enhancing efficiency, improving outcomes, and ultimately enabling better client experiences.
One of the most striking insights from the discussion is how little financial advice workflows have evolved.
Goh highlights a simple but powerful observation: 25 years ago, producing a financial plan was time-intensive. Ten years ago, it still took around 10 hours. Even as recently as two years ago, that same process remained largely unchanged.
This stagnation reflects a broader issue within the industry. While new tools and platforms have emerged, they have often focused on improving individual components—such as CRM systems or modelling tools—rather than fundamentally redesigning the workflow itself.
As a result, advisors are still required to manually connect disparate systems, complete repetitive tasks, and navigate fragmented processes. The cumulative effect is significant: time spent on administration reduces the time available for client engagement.
Fable’s core proposition is to address this inefficiency at its root.
A key distinction in Fable’s approach is the move from tools to agents.
Traditional advice technology can be compared to individual appliances in a kitchen—each performing a specific function. A CRM stores client data, a modelling tool runs projections, and a document generator produces reports. While these tools may become more advanced over time, they remain fundamentally passive.
Fable, by contrast, is designed as an “agent”—an active system that works alongside the advisor.
Using Goh’s analogy, this is less like having a better toaster and more like having a sous chef. Instead of simply executing tasks, the agent helps guide the process, anticipates needs, and contributes to decision-making.
This shift is significant. It transforms technology from a collection of isolated tools into an integrated system capable of managing complex workflows end-to-end.
One of the most compelling aspects of Fable is the scale of efficiency gains it enables.
Through early testing and an EY-backed study, the platform has demonstrated substantial improvements across a range of tasks. These include processes such as meeting notes, fact-finding, compliance checks, and document preparation.
Performance gains vary depending on the task, but consistently fall within double-digit improvements—often ranging from 25% to 70%, and in some cases reaching as high as 95%.
The ultimate goal is even more ambitious: reducing the time required to produce a financial plan from approximately 10 hours to as little as 30 to 60 minutes.
While this represents a dramatic shift, it is not achieved through simple automation. Instead, it results from redesigning the entire workflow, allowing tasks to be completed in parallel and with greater context awareness.
At the core of Fable’s functionality is its ability to understand context and predict needs.
The system integrates with key data sources—such as email, documents, and practice management systems—allowing it to build a comprehensive view of the advisor’s workflow. From there, it begins to anticipate what tasks need to be completed and suggests actions accordingly.
This predictive capability is particularly valuable during client interactions. Rather than waiting until after a meeting to process information, the system can identify gaps, highlight required data, and suggest next steps in real time.
For example, if a key piece of information is missing, the system can flag it during the meeting, reducing the need for follow-up and preventing delays.
Over time, the system becomes more effective as it learns from user behaviour, adapting to the specific processes and preferences of the advisor.
This creates a dynamic feedback loop, where increased usage leads to improved performance.
One of the biggest challenges in financial advice technology is fragmentation.
Most advice practices rely on a combination of core platforms—such as Xplan or Intelliflo—alongside a wide range of smaller, specialised tools. This creates a “long tail” of applications, each handling a specific part of the workflow.
Fable is designed to operate across this fragmented environment.
Rather than replacing existing systems, it integrates with them—using a combination of APIs, robotic process automation (RPA), and other methods to connect different components.
This approach acknowledges a practical reality: advisors are unlikely to abandon their existing systems entirely. Instead, the goal is to enhance how these systems work together, reducing friction and improving efficiency.
By acting as a unifying layer, Fable enables advisors to interact with multiple systems through a single interface, simplifying the overall experience.
Despite its advanced capabilities, Fable is not designed to replace advisors.
A central theme of the discussion is the importance of maintaining a human-in-the-loop approach. In a regulated industry dealing with highly sensitive data, even small errors can have significant consequences.
As Goh explains, a 1–2% error rate is unacceptable in financial advice. This means that AI must operate as a support system, rather than an autonomous decision-maker.
While the system can draft documents, generate recommendations, and automate workflows, final decisions and communications must always involve the advisor.
This reinforces the role of the advisor as the ultimate decision-maker, ensuring that technology enhances rather than undermines professional responsibility.
One of the most interesting implications of Fable is its potential to improve client relationships.
By reducing the time spent on administrative tasks, advisors can focus more on client interaction. This aligns with a broader trend in the industry, where the value of advice is increasingly tied to relationships rather than technical outputs.
In addition, Fable introduces new ways of supporting client engagement.
For example, the system can analyse an advisor’s entire client base and identify opportunities for proactive communication. This helps address a common challenge: advisors tend to focus on their top clients, often overlooking others.
By providing insights across the full client base, Fable enables advisors to deliver a more consistent level of service, improving overall client outcomes.
This shift has the potential to increase both client satisfaction and business efficiency.
Another key innovation is the ability to provide real-time support during meetings.
Fable can analyse conversations as they occur, identifying required compliance elements and ensuring that key information is captured. This reduces the need for post-meeting processing and helps ensure that advice meets regulatory standards.
In some cases, this could allow advisors to complete compliance requirements before the client even leaves the meeting.
This has significant implications for both efficiency and confidence. Advisors can be more certain that they have captured all necessary information, reducing the risk of errors or omissions.
For newer advisors, this also provides a form of guidance, helping them navigate complex requirements and build confidence in their role.
Beyond efficiency, Fable also addresses a broader industry challenge: accessibility.
Currently, only a small proportion of Australians have access to financial advice, largely due to cost barriers. Many more would benefit from advice but are unable to afford it.
By reducing the time and cost associated with delivering advice, AI has the potential to expand access significantly.
However, Goh emphasises that this does not eliminate the need for human interaction. Clients still want to speak with real advisors, particularly when dealing with complex or personal financial decisions.
The role of AI, therefore, is to support advisors—making advice more efficient and scalable—while preserving the human element that clients value most.
The emergence of AI in financial advice is often framed as a question of replacement. Will technology take over the role of the advisor?
The discussion around Fable suggests a different outcome.
Rather than replacing advisors, AI is redefining how they work. By automating repetitive tasks, integrating fragmented systems, and providing real-time support, it allows advisors to focus on what they do best—building relationships, providing guidance, and helping clients make better decisions.
At the same time, it introduces new possibilities for efficiency and scale, enabling the industry to reach more clients and deliver better outcomes.
In this sense, the future of financial advice is not about choosing between humans and machines. It is about combining the strengths of both—using technology to enhance human capability, rather than replace it.
As the industry continues to evolve, those who embrace this shift may find themselves not only working more efficiently, but delivering a fundamentally better experience for their clients.