Artificial Intelligence
Responsible AI at Scale
Responsible AI aligns policy, tooling, and monitoring. Establish model governance, guardrails for data and prompts, bias checks, red-teaming, and incident response. Done right, safety practices speed innovation rather than slow it.
"RAI should enable speed with safety—controls that are practical, measurable, and embedded into daily work."
Core components
- Policies: acceptable use, data handling, escalation.
- Tooling: guardrails, monitoring, bias evaluation, audit trails.
- Processes: reviews, red-teaming, incident management.
Implementation notes
Align controls with risk—more stringent guardrails for sensitive domains, lighter-weight for low-risk contexts. Automate checks where possible (prompt linting, input/output filters), and provide clear playbooks for issues.
Track RAI KPIs such as incidents avoided, bias metrics, and remediation time. Review outcomes regularly to adjust controls that either block progress or allow unacceptable risk.
