Roles of Key Actors in the Lifecycle of Agentic AI Systems

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Building on our previous discussion about OpenAI’s pivotal role in AI development and the importance of its research, it’s crucial to delve into the lifecycle of Agentic AI systems. A deeper understanding of the key actors involved in this lifecycle is essential, especially as we navigate the complexities of AI governance and regulation.

The Concept of Agentic AI Systems

Agentic AI systems represent a significant leap in AI technology, characterized by their ability to pursue complex goals with minimal supervision. Recognizing the diverse roles involved in these systems’ lifecycle is fundamental to understanding their operational dynamics.

The Human Parties in the AI Agent Lifecycle

The lifecycle of AI systems involves various human actors, each playing a crucial role:

  • Model Developers: These are the architects of AI, laying the foundational capabilities and behavior of AI systems.
  • System Deployers: They bridge the gap between AI capabilities and real-world applications, customizing and operationalizing AI systems for specific uses.
  • Users: At the endpoint of the AI lifecycle, users interact with and direct AI systems, significantly influencing their real-time performance.

Model Developers

Model developers are pivotal in the AI development process, tasked with building AI models that power agentic systems. Their decisions crucially shape the AI’s capabilities, behavior, and potential impact.

System Deployers

System deployers play a critical role in the practical implementation of AI systems. They tailor and manage AI systems, aligning them with the specific needs of an application or industry.


Users are integral to the AI lifecycle, employing AI systems for specific tasks and goals. Their interaction with AI systems directly affects performance and outcome, making their role vital in the practical deployment of AI technology.

Interaction and Interdependency Among Actors

The interaction and interdependency among these actors highlight the complexity of AI systems. Coordinated efforts are essential to ensure that AI systems are efficient, effective, and aligned with intended purposes.

Applying Right-Sized Regulation

Understanding the distinction between these actors is crucial for applying right-sized regulation. Future articles will elaborate on how this differentiation is key to effective and tailored governance in the AI domain.


Grasping the roles and responsibilities of model developers, system deployers, and users is essential for comprehending the AI system lifecycle. This understanding forms the basis for future discussions on regulatory approaches and the continued advancement of AI technology.


  • Shavit, Y. et al. (Dec 2023). “Practices for Governing Agentic AI Systems”. OpenAI. Available Online.

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