Scaling AI Safely: Why Governance, Trust, and Resilience Decide Who Wins
About this session
As AI moves from experimental pilots into core business infrastructure, most organizations struggle not with building AI systems but with scaling them safely and sustainably. Technical performance alone is no longer enough. Issues around governance, security, data integrity, operational resilience, and trust increasingly determine whether AI delivers real business value or remains stuck in pilot mode. This session explores why AI scaling fails in practice and what foundations organizations must build beyond models and infrastructure. We will look at AI as a socio-technical system and discuss how governance, security, and resilience must be embedded from the start to enable responsible, scalable adoption across enterprise environments.
Speaker
Key takeaways
- Why most AI pilots fail to scale beyond proof-of-concept
- The critical role of governance, trust, and security in AI success
- What “production-ready AI” really requires beyond models and data