AI Risk Governance: A Practical Framework Through Four Lenses - Model, Data, Deployment & Strategic and Organisational

Join Ichun Lai for Camelot Network's November Expert-Led Workshop:

AI Risk Governance: A Practical Framework Through Four Lenses - Model, Data, Deployment & Strategic and Organisational.

Joined by a panel of industry experts, Ichun will explore what it takes to move beyond AI pilots and achieve responsible, scalable adoption within regulated financial services organisations.

Effective AI governance is built on three foundations: risk, control and trust.

Success requires leaders to make difficult strategic decisions grounded in technical understanding, balancing risk with commercial objectives while building trust across stakeholders, functions and jurisdictions. This is fundamentally a challenge of leadership alignment and organisational execution.

AI risk extends beyond model performance. Organisations must address data quality and integrity, third-party dependencies, governance structures and the limitations of human oversight. Traditional risk frameworks, designed for deterministic systems, often struggle to manage AI's probabilistic nature.

Using a practical framework centred on four lenses - Model, Data, Deployment, and Strategic & Organisational - the panel will explore:

🔶 Why do traditional risk frameworks fall short when governing AI?

🔶 What new risks have emerged through real-world AI deployment?

🔶 How effective has human-in-the-loop oversight proven in practice?

🔶 What does AI-aware risk governance look like in mature organisations?

While regulation and market expectations continue to evolve, inaction carries its own risk. Organisations that invest in governance, capability and informed decision-making today will be best positioned to shape the future of responsible AI and create lasting competitive advantage.