Hiring Agents Is the Easy Part

AI agents are expanding the capabilities and execution power of organizational staff, evolving beyond simple task assistance (Augmentation) to automating the work itself (Automation). The process of hiring an agent mirrors the process of hiring an employee, going through stages of Screening (capability testing), Onboarding (workflow integration), and Performance Review (performance evaluation).

Current technology focuses on building Screening infrastructure to verify the ability to perform specific workflows and Onboarding infrastructure to grant access to organizational tools and knowledge graphs. However, the true bottleneck is the Verification stage, where the quality of results produced by agents is judged and improved through feedback.

The key challenges to solve for successful agent automation are as follows:

• Defining Quality: How do we define and verify efficiency and the organization's implicit standards (Tacit standards), beyond simply whether a task was completed?
• Autonomous Feedback Loops: How do we create a structure where human feedback does not remain in external databases, but agents accumulate knowledge and drive their own learning?
• Data Ownership: When agents learn from enterprise-specific feedback, who owns that data? (Sovereign AI)
• Accountability and Control: How do we define access control for agents and assign responsibility in the event of loss of control?