Report: Building trust in AI for financial advice

The joint Iress and Thoughtworks paper explores how financial advice firms can adopt AI in ways that create genuine value while protecting and strengthening client trust. Drawing on lessons from organisations already navigating AI transformation, it identifies four principles for leaders: build on trust, strengthen organisational foundations, design around complete experiences and learn from real problems before scaling.

This report is for leaders across financial advice who are considering where and how AI can create value, including those responsible for advice, technology, operations, transformation, risk and compliance. It is particularly relevant for organisations looking to move beyond AI experimentation and build trusted, practical capability that can scale.

Financial advice is fundamentally a trust-based profession. Clients rely on advisers to apply judgement and context to decisions whose consequences can last for decades. With only 36% of Australians saying they trust AI, firms need to ensure AI-enabled experiences reinforce rather than undermine the confidence clients already place in their advisers.81% of ANZ consumers have used AI tools to support their online shopping, primarily to offload cognitive tasks like complex product comparisons.

They should first understand how work happens today, identify operational friction, clarify ownership and decision-making, and make sure their data and processes are accurate, accessible and well governed. AI can amplify existing weaknesses, so strong organizational foundations are essential before scaling.

The report draws on real-world lessons from organisations across digital platforms, banking, travel and enterprise technology that are already applying AI in practice. It examines how these organisations are approaching issues such as trust, operating-model readiness, customer experience, experimentation and scaling, and translates those lessons into practical implications for financial advice. It is also informed by external research on trust and attitudes to AI.

Start with one real problem rather than attempting to apply AI across the entire practice. Map a client or adviser journey, identify where friction occurs, choose a specific use case and establish a measurable baseline. Early implementations should be treated as opportunities to learn and refine the approach before wider deployment.

No. The report argues that AI should amplify the human relationship at the heart of financial advice. Its greatest potential lies in reducing administrative work, improving access to information and helping advisers deliver more timely and personalized support while keeping human judgement and accountability central.

Success should be measured against the problem the initiative was designed to solve – for instance, time saved, errors reduced, faster responses, improved adviser capacity or better client experiences. Usage alone is not evidence that an AI initiative is creating value.