Cover Image for No. 56: AI 2030 Online-Agentic Government
Cover Image for No. 56: AI 2030 Online-Agentic Government
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No. 56: AI 2030 Online-Agentic Government

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About Event

AI 2030 Online: Agentic Government is an action-driven event for public sector leaders who are moving from AI ambition to real-world deployment of agentic systems.

As AI agents begin to plan tasks, trigger actions, and coordinate decisions across public systems, the challenge is no longer experimentation—it is execution with accountability. This event focuses on how the public sector can design, deploy, and govern agentic AI that delivers measurable outcomes while remaining lawful, secure, and aligned with democratic values.

Convened by AI 2030, the event emphasizes practical implementation. Participants will engage in hands-on discussions around designing, procuring, governing, and scaling agentic systems that support real public missions—from service delivery and regulatory oversight to public health, climate resilience, and infrastructure.

Participants will leave with:

  • Clear models for human-in-command oversight of AI agents

  • Playbooks for moving from pilots to production-ready agentic systems

  • Practical approaches to embedding Responsible AI into procurement and operations

  • Risk controls for monitoring, auditing, and intervening in autonomous systems

  • Metrics for measuring mission impact, trust, and public value

AI 2030 Online: Agentic Government is built for public sector leaders who are shaping how work gets done in an era where AI agents increasingly act on behalf of institutions—and where responsibility, trust, and impact must scale alongside autonomy.

Become an AI 2030 Member:

https://ai2030.org/apply-to-be-a-member/

Hosted by

AI 2030 www.ai2030.org
AI 2030 is a global initiative committed to mainstreaming Responsible AI by 2030. Through cross-sector collaboration, capacity building, and inclusive programming, AI 2030 empowers leaders, organizations, and communities to harness AI for the benefit of humanity.

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