SIMPLIAgents can retrieve evidence, classify disputes and draft responses far faster than a person. The question for risk teams is not whether to use them, but how to keep control while they do. The answer is design, not hope.
Three levels of control
Work should be routed by risk. Routine, well evidenced cases can run automatically. Cases that cross a policy threshold go to a reviewer. The hardest cases go to experts.
Automate
- Low value
- High confidence
- Complete evidence
- Familiar pattern
Review
- Mid value
- Medium confidence
- Gaps in evidence
- Policy threshold hit
Expert
- High value
- Novel or ambiguous
- Arbitration
- Regulatory sensitive
Principles that build trust
- Permissioned agents. Each agent can read and do only what you have explicitly allowed.
- Source cited output. Every statement points to a record, and missing evidence is stated, not invented.
- Explicit thresholds. Value, confidence, novelty and policy rules decide what needs approval.
- Complete audit trail. Inputs, sources, model versions, approvals and outcomes are recorded.
- Model choice. Use the language model that your security team has approved.
Questions to ask any vendor
- Can you show me the source for every claim in a draft?
- What stops an agent from acting outside its permissions?
- How are approval thresholds set and changed?
- Can I retrieve the full history of a case for an auditor?
- What is your unsupported claim rate, and how is it measured?
Aim for zero. Treat any unsupported AI claim as a defect. Track the rate and set the target at zero.
The takeaway
Transparent AI is not slower AI. When people trust the controls, they can safely let the agents do more of the work.