AI Governance and adoption can’t be achieved with policies alone; they need to be engineered into the technology stack. This session demonstrates how platforms, tools, and automation can help enterprises embed trust, optimize cost, and scale AI securely, while still allowing room for experimentation and innovation.

Key takeaways:

• Embedding compliance-by-design into architecture and platforms
• Automating monitoring, auditing, and bias detection to reduce manual burden
• Making AI decisions understandable for business users, customers, and regulators
• Balancing governance with freedom to experiment
• Evolving governance frameworks dynamically alongside new technologies and regulations