Everyone is investing in AI. Far fewer organizations are investing in what AI needs to deliver on its promise: the underlying infrastructure, processes, and governance that turn a promising pilot into something the entire enterprise can rely on. The companies pulling ahead aren't just deploying smarter models. They're making deliberate decisions about how work gets built, reviewed, and delivered, and they're doing it in a way that holds up under scrutiny from regulators, auditors, and customers who cannot afford for things to go wrong. This session explores what that looks like in practice. Through the lens of a real enterprise transformation, we'll examine what it actually takes to move from fragmented, disconnected development environments to a unified platform that gives leadership visibility, gives engineers confidence, and gives AI the structured foundation it needs to add genuine value. The lessons are less about technology than about mindset; about building systems where safety is the default, accountability is built in, and speed doesn't have to come at the cost of control.

Drawing on Appian’s transition from fragmented delivery tooling to a unified GitLab platform, this discussion demonstrates how combining a single data plane with deterministic process automation builds the exact operational base layer AI needs to scale securely.