AI Governance
We use AI to accelerate analysis and drafting, not to replace accountability. This framework explains how we keep AI-assisted SEO ethical, privacy-safe, and reviewable — with clear human approval gates before anything is implemented or published.
AI outputs are treated as drafts. Final decisions, edits, and publication require human approval and documented checks. Privacy controls are aligned with our Privacy Policy.
Material changes are logged so decisions can be reviewed and explained.
No automated publishing. Human approval is mandatory before deployment.
We minimise data and avoid unnecessary identifiers in AI prompts.
We avoid unverified statements and keep outputs bounded and checkable.
Why AI Governance Matters In SEO
AI can produce confident wording even when information is incomplete. In SEO, that creates risk: inaccurate claims, unclear attribution, privacy issues, or content that drifts outside what your business can genuinely stand behind. Governance exists to prevent those failures — before they reach your website.
What We Optimise For: Safe, Verifiable Output
Our governance focuses on reliability and accountability. AI is used to accelerate early-stage work, but quality is enforced through human review and documented checks.
- Accuracy: AI output is reviewed for factual reliability and clear boundaries.
- Privacy: data is minimised and handled in line with policy.
- Traceability: recommendations and changes can be explained.
- Consistency: language and claims align across trust pages.
For service context, see AI SEO Services.
Want A Clear Starting Point?
Get a technical-first audit focused on inclusion blockers and signal gaps.
Human-In-The-Loop (HITL) Protocol
AI never “self-publishes” on our workflow. Every meaningful output must pass review gates. This is how we reduce errors, keep claims bounded, and protect privacy.
1. Input Control
- Minimise data; remove unnecessary identifiers where possible.
- Use prompts designed to keep scope tight and avoid overreach.
- Confirm the output goal before generating drafts.
2. Output Validation
- Check for factual uncertainty and remove unsupported statements.
- Enforce intent boundaries (no mixed-page messaging).
- Apply claims discipline: no guarantees, no invented proof.
3. Editorial Approval
- Human reviewer approves before publish or implementation.
- Material edits are logged with rationale (what/why/when).
- High-risk topics trigger senior review escalation.
Want The Full Policy Context?
See how privacy and service boundaries are defined in our trust pages.
What We Use AI For (And What We Do Not)
Transparency matters. AI can be helpful when used with boundaries. This section clarifies typical uses and explicit exclusions.
We Use AI For
Assisted drafting and structured thinking — always reviewed before use.
- Summarising large inputs into structured notes
- Generating draft outlines and alternative wording
- Detecting patterns across queries and content inventories
- Creating checklists to standardise QA
We Do Not Use AI For
Anything that would bypass accountability or introduce unverifiable claims.
- Auto-publishing content without human approval
- Inventing statistics, testimonials, or case details
- Creating misleading urgency or exaggerated promises
- Processing unnecessary sensitive personal data
Human Review Focus
Where reviewers apply strict checks before implementation.
- Claims and wording that could be interpreted as guarantees
- Any content that references policy, privacy, or compliance
- Any client-specific details or sensitive operational data
- Headlines, definitions, and “best practice” statements
Privacy And Data Handling
We treat privacy as a governance requirement, not a marketing line. Data handling is designed around minimisation, access control, and clear purpose.
Prompt Hygiene
Prompts are written to keep scope controlled and reduce accidental disclosure.
Data Minimisation
We only use what’s necessary for the task and avoid unnecessary identifiers.
Access Control
Access is limited to authorised team members based on role and task.
Policy Alignment
Processing and disclosures align with our published trust pages
Accountability, Corrections, And Escalation
If anything appears unclear or incorrect, it is reviewed under the same governance gates. We prioritise correction and transparency over defensiveness.
How Issues Are Handled
- Flag: content is flagged for review (internal QA or external feedback).
- Verify: the claim or statement is checked; unsupported wording is removed or rewritten.
- Document: the change is logged with a clear reason and timestamp.
- Escalate: higher-risk areas trigger senior review before republishing.
Learn more about our team context on the About page.
Governance Question Or Concern?
Use our contact page for governance-related queries and trust-page feedback.
AI Governance FAQs
Clear answers about how AI is used, how outputs are checked, and how privacy is protected.