Episode 3: Why Do Most AI Projects Fail?
AI is helping wealth firms shift from reactive to proactive risk management.
Continuous monitoring improves the efficiency and scalability of controls and assurance activities.
Reconciliation processes are a high-value AI use case, reducing manual effort and improving exception management.
Industry research suggests that a large proportion of AI pilots fail to reach production. Common reasons include unclear objectives, poor governance, lack of stakeholder buy-in, and focusing on technology rather than business outcomes.
Chris shares lessons from the financial services sector and highlights practical AI use cases that are delivering measurable value today, including reconciliation exception analysis, risk and control monitoring, compliance assurance, evidence gathering, and operational efficiency improvements.