Programme outline
Learning objectives
By the end of the course, participants will be able to:
- Evaluate ethical, operational and governance risks associated with Artificial Intelligence (AI)-enabled initiatives using Monetary Authority of Singapore (MAS)-aligned responsible AI principles.
- Apply AI governance frameworks, including AI lifecycle, AI risk materiality and data governance concepts, to practical financial services scenarios.
- Recommend appropriate governance, monitoring and human oversight measures to support responsible Generative AI (GenAI) adoption across business functions.
- Develop practical solutions and implementation strategies to strengthen responsible AI adoption within their own organisations.
Day 1
- Programme introduction, learning objectives & Workplace AI Governance Challenge
- AI Governance Foundations & MAS / Project Mind Forge Context
- Responsible AI & Ethical Decision-Making (FEAT principles and AI credit risk case study)
- AI Governance, Data Governance & Third-Party AI Risk (DBS & wealth copilot case studies)
- AI Risk Materiality, Governance Controls & AI Lifecycle Management
- Workplace group project: AI Governance Challenge Discussion & Solution Development
- Group project presentation, facilitated debrief & peer learning
- Programme reflection, key takeaways & workplace action planning
Assessment
- Group project discussion & presentation