Sumeet Chabria

Financial institutions that are looking to generate business outcomes with artificial intelligence (AI) must identify use cases that drive adoption by creating a strategic framework that aligns business value, data readiness and risk management. The goal is to achieve production-grade deployment that delivers a return on investment. The challenges that institutions face: data ecosystems are often fragmented and unprepared for AI scale, and risks—bias, privacy, security and regulatory compliance—can derail adoption if not addressed early. Among the points to be discussed by panelists:

• Aligning AI use cases with business value
• Data readiness as a foundation
• Risk management and responsible AI
• Scaling AI beyond pilots