RESPONSIBLE AI
AI that assists within governed boundaries.
ZoikoSuite uses AI-enabled capabilities to help classify, summarize, forecast, recommend, prioritize, and support decisions. Material actions remain subject to the policy, authority, evidence, and human review controls defined for the underlying workflow.
AI AT A GLANCE
Six things worth knowing before you read further
Assistive role
AI supports governed work; it does not silently become the source of truth.
CURRENT / SCOPED
Human authority
Where material review or approval is required, the authorized human/workflow remains responsible for the decision.
CONFIGURATION DEPENDENT
Data use
How prompts, records, and outputs are processed is disclosed through approved privacy/contract/provider sources.
REGISTRY-DRIVEN
Transparency
AI interaction and generated-content disclosures apply where required by feature, role, and jurisdiction.
JURISDICTION DEPENDENT
Evidence
Material AI use should preserve provenance, model/provider context, policy basis, and review outcome as designed.
IMPLEMENTATION-STATUS QUALIFIED
Challenge / concern
Users can report an AI concern; eligible material workflows may expose human review or correction paths.
AVAILABILITY QUALIFIED
AI CAPABILITY & AUTHORITY MODEL
Governed intelligence: AI assists after control boundaries are defined
| Capability Class | AI May | AI May Not | Authority |
|---|---|---|---|
| Classify / extract | Propose labels, clauses, obligations, or metadata with provenance/confidence. | Silently overwrite source records or finalize material classifications when review is required. | Authoritative record owner |
| Summarize | Condense governed source material, citing source context where supported. | Create a new source of truth merely because a summary exists. | Underlying source record |
| Forecast / score | Estimate exposure, probability, severity, priority, or scenarios. | Present a prediction as certainty or automatically trigger prohibited material action. | Policy thresholds + reviewer |
| Recommend | Surface options, rules, evidence, and suggested next steps. | Bypass required approval, delegation, segregation of duties, or jurisdiction checks. | Named approver / policy engine |
| Reconcile / match | Suggest matches and exception-resolution paths. | Finalize material reconciliation when policy requires governed review/evidence. | Configured workflow |
| Flag / detect | Identify anomalies, exceptions, or patterns. | Modify immutable truth or silently deny a person solely from an unreviewed signal. | Authorized review process |
WHERE AI MAY APPEAR
Capability categories, not speculative promises
| Capability | Public Boundary Copy | Do Not Imply |
|---|---|---|
| Anomaly detection | Flags unusual financial, payroll, compliance, or workflow patterns. May score/prioritize; may not alter source truth. | Autonomous fraud guilt, automatic enforcement, or certainty. |
| Forecasting | Estimates exposure while preserving scenario/model/confidence context. | Guaranteed outcomes or professional advice. |
| Reconciliation assistance | Suggests matches and exception-resolution paths; final reconciliation remains governed and evidential. | Automatic finalization outside the approved workflow. |
| Compliance risk scoring | Prioritizes obligations by severity, proximity, and evidence sufficiency; action thresholds remain human/policy-defined. | Regulatory determination without approved review. |
| Document & obligation extraction | Proposes clauses, obligations, and metadata; material use requires provenance/confidence and review where configured. | Legal conclusions or silent contract changes. |
| Decision support | Surfaces relevant rules, evidence, and options at approval points; cannot bypass authorization. | Independent decision authority. |
HUMAN OVERSIGHT & DECISION AUTHORITY
Not every output is reviewed — the boundary is stated by use case
| Authority State | Meaning | UI Treatment |
|---|---|---|
| Informational | AI output is advisory/informational; no action occurs from output alone. | Labeled "Assistive output" |
| User confirmation | User must confirm before a reversible action proceeds. | Confirmation step with editable fields |
| Qualified review required | A named role must review/approve before material action. | Reviewer identity, rationale, audit reference |
| Policy/SoD gate | Configured policy, delegation, or segregation-of-duties control must pass. | Gate state visible; AI cannot bypass it |
| Human review available | An eligible decision/outcome can be escalated for human review or correction. | Review CTA, status, response expectation |
| Prohibited autonomy | AI cannot perform the defined action autonomously. | No hidden automation path; disabled state |
AI OUTPUT LIMITATIONS & USER RESPONSIBILITIES
What users should verify before relying on an output
| Topic | Required Guidance |
|---|---|
| Probabilistic output | AI-generated classifications, summaries, predictions, and recommendations may contain errors, omissions, or uncertainty. |
| Source verification | Users should verify material outputs against authoritative records, cited sources, and qualified review where required. |
| Confidence/context | Confidence, scenario, or provenance signals are never guarantees. |
| Corrections | Corrections must update the governed workflow/source record where appropriate — editing a generated summary alone does not silently rewrite source truth. |
DATA, PRIVACY, TRAINING & IMPROVEMENT
The highest-risk copy area on this page
No blanket "we never train on your data" or "we use your data to improve AI" statement is made unless it is true for every scoped feature, provider, deployment, and approved contract.
| Field | Required Behavior |
|---|---|
| Data types used | Prompts/instructions, governed source records, retrieved context, output, feedback, or telemetry — described at a useful, approved level. |
| Provider role | First-party model, third-party model/API, customer-selected provider, local/customer-controlled deployment, or not publicly named. |
| Training / model improvement | Exact state: not used; may be used under stated conditions; customer-configurable; provider-specific; unknown/blocked from publication. |
| Retention | Linked to the approved retention statement, or explained as varying by feature/provider/configuration — never invented. |
| Transfers / location | Cross-linked to Privacy Policy, DPA, Subprocessor List, and Data Residency — residency and transfer are never treated as the same concept. |
TRANSPARENCY, AI INTERACTION & GENERATED CONTENT
Disclosure that precedes reliance — not buried in a footer
| Scenario | Required Capability | Publication Rule |
|---|---|---|
| Direct interaction with AI | Contextual label before or at first interaction when required. | Enabled by feature/role/jurisdiction matrix. |
| AI-generated or manipulated content | Visible label and machine-readable marking capability where legally required and technically applicable. | Status-qualified — no universal marking claim without implementation proof. |
| Emotion recognition / biometric categorization | Disclosure and stricter eligibility controls where applicable. | Default page must not imply ZoikoSuite offers these unless verified. |
HIGH-IMPACT, RESTRICTED & PROHIBITED AI USES
The control concept lives here — the binding taxonomy lives in the AUP
| Category | Legal-Page Treatment | Authoritative Destination |
|---|---|---|
| Prohibited by law / policy | ZoikoSuite AI may not be used for uses prohibited by applicable law or the AUP. | Acceptable Use Policy |
| High-impact / regulated use | Requires explicit eligibility/review/configuration state before use. | Trust Responsible AI + product policy + contract |
| Autonomous material action | Reiterates the prohibited-autonomy boundary unless a specifically approved workflow says otherwise. | Product authority policy |
| Security abuse / model exploitation | Cross-links Security Disclosure and AUP, preserving the good-faith research route. | Security Disclosure + AUP |
THIRD-PARTY MODELS, PROVIDERS & TOOLS
Provider names age quickly — this stays registry-driven
| Element | Required Treatment |
|---|---|
| Provider disclosure | Named only where Legal, Procurement/Security, and Product approve public disclosure. |
| Subprocessor status | If a provider processes customer personal data as a subprocessor, the Subprocessor List remains authoritative. |
| Provider outage | UI degrades safely — no silent fallback to a different provider if that changes data/legal terms without approved behavior. |
SECURITY, MISUSE & AI INCIDENT HANDOFF
AI-specific context is evidence, not a separate enforcement regime
| Risk Area | Required Public Message | Handoff |
|---|---|---|
| Prompt/data injection | Users should not treat untrusted content as authoritative instructions. | Security Overview / Trust Responsible AI |
| Unsafe or unexpected output | Concern/report route with feature, context, and output-reference fields. | AI concern workflow |
| Good-faith research | Routes to Security Disclosure terms. | Security Disclosure |
HUMAN REVIEW, CORRECTION & AI CONCERNS
A structured, minimum-data-collection report
JURISDICTION & REGULATORY NOTICE MODEL
Effective-dated notices only where they materially change expectations
| Field | Required Value |
|---|---|
| Jurisdiction / region | Country, state/province, or regulatory bloc. |
| Feature / use case | Specific AI capability or class — never "all AI." |
| Effective date | Exact date and version of analysis. |
| Implementation state | Implemented; configuration required; legal review; planned; not applicable; unsupported. |
FREQUENTLY ASKED