AI-driven outbound and customer communications fail compliance review for a predictable set of reasons: PII flowing through prompts and logs without redaction controls, no approval gate before AI-drafted messages hit the inbox, no audit trail if something goes wrong, and no RBAC to limit who can trigger what at scale. These aren’t edge cases — they’re the blockers that stop legal and compliance from signing off, and they’re what cause teams to abandon AI comms programs after the first incident rather than fix the infrastructure that produced it.
We build the governance layer that makes AI comms safe to scale: PII redaction rules, approval workflows with defined reviewer roles, prompt and output logging with configurable retention, and RBAC design so access matches accountability. The output is practical — built to keep teams moving fast while satisfying the controls that legal actually needs. We deliver the rules engine, the workflows, the logging setup, and an incident playbook, then hand the system over to whoever owns compliance and ops internally.
The threat model we work from covers four categories: data leakage (PII in prompts or logs), output risk (off-brand or non-compliant AI-drafted content), access abuse (AI comms triggered by unauthorised users or at unauthorised scale), and auditability gaps (no record of what was sent, by whom, to whom, and when). Each control we build maps to one or more of these. PII redaction is applied at the prompt-construction layer before data reaches any AI model; it is not a post-processing filter on the output. Approval workflows are designed with escalation paths, not just approval/reject buttons — reviewer overload is a real failure mode and the workflow needs to handle it.
Access requirements are narrow but specific. We need read access to the systems where contact data lives and write access to the workflow and logging infrastructure being built. We do not need, and will not request, broad CRM admin access for this engagement; scoped credentials are the right posture and we design accordingly. Logging configuration involves decisions about retention periods, storage location, and who holds decryption keys — these are compliance decisions that the client’s legal or data team needs to own, and we facilitate the decision rather than make it for them. The access register and logging configuration document are part of the handover package.
This layer is not the right investment for every team. If AI comms volume is low — a handful of manually reviewed messages per week — a simple approval step in your existing workflow tool is sufficient and adding a purpose-built governance layer is overhead you do not need yet. If your organisation does not have a named compliance or legal contact who will own the rules post-handover, the controls will drift and the investment is wasted. We will surface both of these in discovery. The governance layer earns its cost when AI comms volume is high enough that manual review at every step is genuinely the bottleneck, or when regulatory exposure — GDPR, CAN-SPAM, sector-specific rules — makes the audit trail materially important.
Operational ownership after handover sits across two roles. The compliance or legal owner holds the rules definitions — PII categories, approved message types, retention periods — and reviews them when the business or regulatory context changes. The ops or RevOps owner watches the operational monitoring: approval queue depth, log storage consumption, RBAC exceptions, and any incident flags. We deliver an incident playbook that covers the four most likely failure scenarios — a PII leak, an unapproved message sent, a logging outage, and an RBAC misconfiguration — with step-by-step response procedures. The playbook exists so that when something goes wrong, the response is a documented process rather than an emergency call to us.