Delivering the Productive State: A 12-Month Review of Intelligent Automation

The initial hype and excitement surrounding Generative AI have begun to settle, giving way to a more grounded realisation: true productivity gains require more than just better tools. Following the government's commitment to build an agile and efficient state, over the past 12 months, the public sector has moved from the experimentation phase into a challenging period of operational reality of delivering measurable outcomes. This session provides a candid review of that transition.

• How do we connect disparate data points across business processes to achieve the joined-up services targeted by the national roadmap?
• How do we choose the most appropriate AI models for specific tasks to achieve maximum efficiency and lower energy waste?
• How do we automate the application of structure to AI outcomes to ensure that productivity is not lost through manual sifting and re-contextualisation?
• How do we embed organisational and operational context within LLMs to ensure we gain intelligence rather than just generic summaries?
• How do we measure the productivity dividend of AI to ensure it is actively contributing to the government's goal of driving national growth?