Monitor agreed metrics
Review processing time, recommendation accuracy, and validated exceptions against the baseline. Metrics are selected for the process.
OPRYNA · AI WORKFORCE
AI Agent Optimization
AI Agent Optimization uses operating results and team corrections to improve business rules, monitor exceptions, and support expansion after an agreed pilot evaluation.
Performance reviews continue after the pilot
Refine rules with owners
Use team corrections to refine documented business rules and retest affected cases. Authority changes require company approval.
Expand the playbook
Reuse a validated workflow in another branch, plant, or process with its own rules, access permissions, and acceptance measures.
WORKING TOGETHER
A clear starting point
Regular performance reports inform the next decision. Expansion follows measured results and company approval; pilot metrics are a measurement plan, not guaranteed outcomes.
Review authority and approvals →
Explore related work
AI Agent Optimization: frequently asked questions
What does AI Agent Optimization cover?
AI Agent Optimization uses operating results and team corrections to improve business rules, monitor exceptions, and support expansion after an agreed pilot evaluation.
Who approves the agent’s actions?
Your company agrees authority for each process. Pilots start at L0–L1; higher authority requires approval and can be lowered at any time.
What should we prepare first?
Prepare one process owner, an IT contact, and 20–30 document samples. An NDA precedes company data transfer; samples may be anonymized.
For an external AI governance reference, see NIST AI Risk Management Framework.
Choose one process to discuss
Map the work, confirm evidence, and agree what a useful pilot should measure.