Risk FAQ
Plain-English answers for Isle of Man organisations that want useful AI adoption without losing control of sensitive data, professional judgement or auditability.
Not by default. The first step is to define data boundaries: public, internal, confidential, personal/client-sensitive or restricted. Sensitive workflows may need redaction, approved tooling or a private stack before live use.
No. The sprint is designed around human review. AI may help prepare, retrieve, draft, summarise or structure work, but regulated judgement, client advice and final decisions stay with the accountable people.
We start with constrained workflows, visible source material and review points. For knowledge retrieval, the preference is source-linked answers that staff can inspect rather than unsupported free-form output.
The team should have a current-state workflow map, baseline assumptions, a tested workflow or implementation design, risk notes, staff guidance and a recommendation to scale, improve, pause or stop.
No. AI Solutions IOM provides operational workflow, training, governance and implementation support. Legal, regulatory and data-protection advice should remain with the organisation's appointed advisers and accountable officers.
Sometimes, but the controls matter. The right answer may be a private knowledge workflow, access controls, audit logs, redaction, approved sample data or keeping the work out of public AI tools entirely.
Approve a named workflow, owner, data boundary, human-review point, success measure and stop/go decision date. Avoid approving a vague AI pilot with no operational baseline.
No. Funding eligibility and approval must be checked with the relevant scheme at the time of use. The practical next step is to scope the business case clearly enough for a funding conversation if one is appropriate.
The safer first move is to choose one workflow, agree what data can be used, keep human review explicit, measure whether the work improves and stop if the evidence is weak.
Next step
Book a short fit check and we will pressure-test whether AI can genuinely help, what data is safe to use, and who needs to be involved.