Understanding what AI can do is no longer the primary challenge for government. The real work is reducing system friction—so AI can be adopted in ways that are safe, lawful, governed, and repeatable, moving beyond pilots into durable, system-wide capability.
In this session, Dan shares practical, real-world experience establishing the foundations needed for scale: the governance, assurance, operating models, and enabling components that turn experimentation into production-ready adoption across government.
Dan delivers a short presentation, followed by a live Q&A moderated by Ross.
What you’ll hear about
- Why AI demands modernised governance, risk management, and assurance
- The system components required to scale AI: policy, frameworks, capability, platforms, and operating models
- How friction is reducing between people and AI—and what this means for the path from idea to production
- The role of people, partnerships, and problem-led collaboration in enabling scale
- Future scenarios—and what effective partnerships could look like in a mature, low‑friction system
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