Test AI risks, apply guardrails and turn control gaps into audit-ready evidence.
Connect AI and LLM test findings with guardrails, control owners and remediation evidence. Agree which systems, data and requirements are in scope before assessment. Start when AI adoption outpaces control ownership or an assurance review needs traceable evidence.
Infrastructure and identity controls belong to Cloud security & IAM; web, code and supply-chain testing to Exposure validation & AppSec. For enterprise AI policy and roadmaps, see AI strategy & governance.
Define the test scope and acceptance evidence together, rather than treating AI risk as a generic application review.
Agree test scenarios and exclusions for the AI systems in scope.
Confirm prompt injection, sensitive-data leakage and unsafe tool-action tests before work.
Connect relevant requirements to technical and organisational controls.
Review agreed guardrail settings and AI traces against the intended behaviour.
Give users role-based guidance on approved AI use and reporting concerns.
Example engagement pattern: an enterprise AI assistant needs clear data boundaries, control owners and a repeatable evidence review.
Agree the AI and data inventory, rules of engagement and test-data handling.
Run the agreed scenarios and document their context, evidence and limits.
Rank the risks and agree guardrail or process changes with accountable owners.
Check approved changes and agree how evidence is revisited as AI use changes.
AI Governance is a Linkfields gateway and guardrails offering built on Portkey + Opik, not Linkfields-owned tools. Reusable accelerators support control mapping and evidence readiness; they are delivery artefacts, not standalone software.
LINKFIELDS PRODUCTConnect guardrails, cost and tracing with specialist configuration and trace or evaluation review. Confirm the Linkfields configuration layer and integrations in a walkthrough.
Tailor control-mapping templates to connect requirements, owners, gaps and evidence.
Structure evidence collection and review. Control owners approve and refresh evidence at the agreed cadence.
Agree the applicable requirements with risk and legal owners before mapping controls. Assessment does not certify compliance or replace legal advice.
Agree whether POPIA safeguards, operator arrangements and cross-border processing apply to the AI systems assessed.
Agree whether ISO/IEC 27001:2022 or NIST CSF 2.0 is the relevant mapping basis; ISO control mapping is not certification.
Confirm applicable OWASP AI/LLM guidance and any ISO/IEC 42001 mapping before including them in the assessment.
The next step is a scoping discussion about AI systems, control objectives and the evidence you need. Do not send credentials, personal information or confidential test findings.
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