Artificial intelligence (AI) is implemented across various areas within organisations, including forecasting, workflow support, content generation, and decision assistance. However, in many large and regulated organisations, AI has yet to progress beyond pilots and fragmented experiments into standard operating practice. This ongoing research-in-progress examines that gap as an organisational and governance issue rather than a technical challenge.

The study explores key areas such as operating model design, decision rights, workflow integration, human oversight, governance maturity, and workforce implications to understand how AI-augmented decisions can be scaled effectively. Another issue is that AI is frequently presented not only as a productivity-enhancing tool but also as one that can reduce labour costs, thereby creating friction between the ambitions of automation and the desire for accountability, trust and organisational legitimacy.

The project adopts a mixed-methods approach, including purposive interviews with senior leaders and an exploratory survey regarding AI adoption, governance, and organisational readiness. It aims to provide a useful roadmap for organisations that wish to migrate AI projects from successful pilots to an auditable, defensible and operationally embedded practice, without reducing governance to a post hoc control exercise.