The AI architect role is becoming more visible, and the scope varies across organisations. The challenge is defining what the role owns, where it sits, and how it works with existing architecture, data, security, risk, and business teams. Three pressure points need clarity. - Role definition matters because the position can span solution architecture, data architecture, governance, integration, security, vendor selection, and business process design. - Interfaces matter because the role must connect teams while respecting existing responsibilities. - Skills matter because technical depth needs to be combined with judgement around controls, delivery choices, and operational boundaries. The working question is simple: how do we define the AI architect role so it becomes useful, credible, and connected to delivery? If this role is emerging in your organisation, let’s compare how others are defining it and where they are placing it.
.png)
