Why Attend (Procurement & Commercial)

As government shifts to platform-based services, delivery is fundamentally changing. Systems are no longer owned by single departments, but built on shared infrastructure, powered by cross-government data, and shaped by automated decision-making. While this enables scale and efficiency, it raises a critical question: when something goes wrong, who is accountable? This panel will explore real-world experiences from senior leaders operating in complex, cross-government environments. Rather than theoretical discussion, speakers will reflect on situations where accountability was unclear, decisions had to be made under pressure, and existing governance models were tested.

• When systems are jointly owned and continuously evolving, how should accountability be defined?
• How do we assign responsibility when decisions become automated?
• Are current governance, audit, and assurance models fit for platform-based government?
• What practical steps can leaders take now to prepare for failure, not just delivery success?

Despite efforts to reform, central government still operates largely in departmental silos, limiting opportunities to deliver joined-up, efficient systems. With pressure mounting to do more with less, 2026 marks a shift toward converged operating models and cross-government collaboration. Yet barriers remain around data-sharing, supplier management and investment decisions. This session brings together leaders to explore how government can move from isolated initiatives to a system-wide approach. What practical steps would enable data sharing and align strategy across departments? 

• How can government overcome cultural and organisational barriers to effective data sharing?
• What does a realistic, joined-up operating model look like across departments?
• How can shared services reduce duplication while respecting departmental autonomy? 

AI adoption across central government has moved from pilot projects to an operational expectation. But beneath the surface, a harder question is emerging: are we truly transforming services, or simply layering AI onto systems that aren’t fit for purpose? This keynote panel challenges the narrative of progress and asks leaders to confront the gap between ambition and delivery. With growing pressure to demonstrate value under tight fiscal conditions, departments must move beyond proof-of-concept and into measurable, citizen-facing outcomes. This session will examine what is actually working, what is falling behind, and what must change to deliver AI at scale. From data quality and legacy constraints to governance, procurement, and accountability, speakers will explore the ways government is structurally ready for AI, and what it will take to get the rest of the way there.

• How are departments moving from pilots to scalable, outcome-driven AI adoption?
• What governance models enable safe, but agile, AI deployment?
• How can policy, procurement, and delivery functions align to avoid duplication?
• How are legacy systems being addressed to ensure AI tools are effective?