AI Unplugged
An Interactive Introduction for Financial Services & Insurance
From Buzzwords to Real-World Impact in Just Half a Day
Artificial Intelligence is no longer a futuristic buzzword; it’s a driving force of change in the financial services and insurance industries. From fraud detection to customer personalization, AI is reshaping how organizations compete, comply, and deliver value. Yet, for many professionals, AI feels abstract or overly technical. This short, engaging program is designed to demystify AI, explain how it really works, and show its direct impact on FSI.
Participants will leave with a practical understanding of AI opportunities, risks, and governance essentials — and a clear idea of where AI could help in their own work.
Learning Outcomes
By the end of this half-day session, participants will be able to:
- Explain the difference between AI, machine learning, and generative AI.
- Understand in simple terms how AI systems learn and make predictions.
- Identify practical FSI use cases such as fraud detection, underwriting, robo-advisors, compliance, and ESG analytics.
- Experiment with AI tools through guided exercises and demos.
- Recognize key challenges in AI including bias, explainability, and compliance.
- Appreciate the role of AI governance in ensuring ethical, transparent, and regulatory-aligned adoption.
Prerequisites
- No prior technical knowledge required.
- Basic familiarity with FSI processes (banking, insurance, compliance, or investment) helpful but not mandatory.
Detailed Outline
1. Welcome & Icebreaker
- Group activity: Match AI buzzwords to FSI use cases.
- Setting the tone: AI isn’t science fiction; it’s already embedded in everyday financial services.
2. What is AI Really?
- Breaking down the jargon: AI vs. Machine Learning vs. Generative AI.
- Examples from FSI: fraud detection, credit scoring, chatbots, and automated claims processing.
- Short demo of AI tools applied to a financial scenario.
3. How AI Works (The Simple Version)
- Explanation of how AI models are trained on data (patterns, predictions, and outputs).
- Analogy: AI as “teaching a junior analyst at scale” — it learns by example.
- Visual walk-through: From input data → model training → prediction or generation.
- Discussion of limitations: garbage in, garbage out; bias; lack of context.
4. Hands-On with AI
- Demonstration of how generative AI tools can automate real 9-5 tasks..
- Interactive exercise: Participants craft prompts for a financial task and compare results.
5. Opportunities, Risks, and Governance
- Case study: AI in credit scoring — opportunity vs. bias risk.
- Regulatory landscape: global trends (EU AI Act, U.S. regulators, data privacy laws).
- AI Governance Essentials: Why oversight, transparency, and accountability are critical in FSI.
- How governance frameworks protect institutions from reputational, legal, and financial risk.
6. The Future of AI in FSI
- What’s next: AI agents, ESG analytics, fraud prevention, and hyper-personalized products.
- Group discussion: Where participants see AI opportunities in their roles.
- “AI won’t replace you — but professionals who know how to use AI will.”
7. Wrap-Up & Q\&A
- Key takeaways recap.
- Final Q\&A session for clarifying concepts and addressing myths.
- Take-home: “AI Starter Playbook for FSI Professionals” — a one-page checklist of do’s, don’ts, and governance reminders.
Duration
Half-Day (Approximately 3.5–4 hours)
Practical, connected learning
My wider training approach brings hands-on implementation and systems thinking together, connecting technology with real operational needs.