Putting agentic AI systems to work: What practitioners reveal about deployment and governance

Somewhere in a codebase, AI agents are continuously scanning for security flaws, rewriting buggy code, and supporting incident response actions. Somewhere in a government department, another AI agent is sorting incoming correspondence, determining which legal provisions apply to a query, help make planning and permitting processes more efficient.

These are real-world examples of how organisations are already putting agentic AI to work. Agentic AI generally refers to systems composed of multiple co-ordinated AI agents that can break down tasks, collaborate, and pursue complex objectives autonomously over extended periods with limited human oversight. They are attracting growing attention as organisations explore how these systems can unlock new opportunities for innovation and productivity.

But how are different organisations using agentic AI in practice? What are these early applications revealing about the distinctive capabilities of these new AI systems? And what governance approaches are they adopting to manage these systems responsibly? To explore these questions, we spoke with practitioners in 25 organisations across 11 countries, including frontier developers, enterprise deployers, public sector organisations and academic institutions to examine practical implementations as well as perceived benefits and challenges of agentic AI systems.

The resulting OECD working paper, Agentic AI in organisations: Early insights from practitioner interviews examines how agentic AI systems are being developed and deployed in real-world contexts. Building on The Agentic AI Landscape and Its Conceptual Foundations, which examined how AI agents and agentic AI are defined across the literature, the paper offers an illustrative snapshot of how organisations are currently deploying agentic AI systems in practice and what they are learning in the process.

Here are some of the lessons emerging from those conversations.