I in Banking: A Playbook for Success – Euromoney released a new report on AI implementation in banking. It’s clear that while the hype is real, a strategic and cautious approach is essential. Banks are making strides in leveraging generative AI (GenAI) and agentic AI, but there are key considerations for effective and responsible deployment. Key Takeaways:

✅ Embrace Flexibility: The AI landscape is rapidly evolving. Banks need to be agile, ready to switch between LLMs and vendors.
✅ Centralize Strategy, Devolve Execution: A strong central AI function is crucial for oversight, but empowering business units drives innovation and practical use cases.
✅ Invest in People: Upskilling employees across the organization is just as important as hiring top AI talent. Everyone needs to understand how to use these tools effectively.
✅ Strategic Vendor Selection: Carefully evaluate AI models based on performance, security, and cost. Don’t always assume the biggest LLM is the best fit.
✅ Prioritize Trust: Especially in customer-facing applications, prioritize building trust through rigorous testing and safeguards. Start with low-risk use cases and gradually expand.

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