AI policy examples
- AI acceptable use
- AI model and system governance
- Human oversight and escalation
- Responsible AI and risk assessment
- AI vendor risk
- AI incident response
- Training data and data usage governance
AI & Technology Governance and Policy Services
Make your policies and governance documentation reflect how technology is actually used. AuditPartners reviews gaps, responsibilities and control coverage, and supports agreed updates to policies, AI inventories and risk registers.
Governance that reflects actual use
When a policy review helps
Policies are useful only when people can apply them to real decisions. A focused review helps when the written expectations and day-to-day practices have drifted apart.
- Staff are adopting AI tools or agents without consistent ownership and approval.
- Cloud services, vendors or data flows have changed since the last policy review.
- Teams interpret the same policy differently or cannot identify the decision owner.
- Exceptions accumulate without expiry dates, risk acceptance or follow-up.
- A customer or internal audit request exposes missing inventory or control documentation.
- Existing policies describe a process that no longer matches the way work is done.
What we review
We agree the documents, business areas, systems and reference criteria first. Interviews, policy records and selected workflow evidence help us understand where documentation supports practice and where further testing would be needed.
Policy gap analysis
Compare documented expectations with how selected technology is actually used. Identify unclear instructions, conflicting documents and gaps in the agreed criteria.
Ownership and RACI
Review who is responsible, accountable, consulted and informed for approvals, controls, exceptions and escalation. Check whether those responsibilities are workable.
Control coverage
Trace relevant policy expectations to control owners and expected evidence. Separate a stated requirement from an implemented or tested control.
AI inventory
Review purpose, system ownership, models, vendors, data, access and lifecycle status for the selected AI use cases. Identify unrecorded use and unknown fields.
Risk register
Check whether risks connect to systems, impacts, control responses, decision owners and recorded acceptance or treatment decisions.
Exceptions and review cadence
Review how exceptions are authorized, time-bounded and revisited, and how policy owners respond to changes in technology or risk.
What we help update
The following are examples, not a promised policy suite. We focus on the documents you need and the responsibilities your team can sustain. Any mapping to reference criteria is scoped and does not imply that frameworks are equivalent.
IT policy examples
- Information security
- Access control
- Change management
- Logging and monitoring
- Vendor risk management
- Data classification and retention
- Business continuity and disaster recovery
- Secure software development
Deliverables
The engagement defines which updates and templates are included, who must approve them and which unresolved decisions remain with management.
Policy gap report
Observed gaps and ambiguities, their supporting evidence and the boundaries of the review.
Prioritized update plan
Recommended changes, dependencies and ownership decisions for management to consider.
Agreed policy updates
Revisions to the documents included in scope, with open decisions identified for your approval.
Inventory and register templates
Structures to record AI use, ownership, dependencies and risk decisions, adapted where agreed.
Ownership and review model
Proposed responsibilities, review triggers, exception handling and escalation arrangements.
Evidence and limitations
Policies are design evidence only. A policy states an expectation; it does not show that the control is implemented or has operated effectively. Operating effectiveness requires testing of relevant records over an agreed period.
We distinguish documented design, observed implementation, tested operation and missing or unknown evidence. Conclusions are limited to what was reviewed and tested; a policy review alone does not provide an operating-effectiveness conclusion.
Agreed updates do not guarantee compliance, certification or acceptance by an external auditor. Management owns approval, communication and operation of policies. Legal interpretations and jurisdiction-specific obligations require appropriate legal advice.
Compare assessments and internal audits for control testingWho it is for
AI owners, security and technology leaders, risk teams and internal audit functions that need clearer governance documentation. Smaller teams can focus on a few essential policies; larger organizations can scope specific functions, systems or shared responsibilities.
There is no employee-count minimum. The right scope depends on how technology is used, the risks involved and the decisions your documentation needs to support.
AuditPartners delivers the review and agreed updates. RiskAssist™ is supporting technology; human professionals own judgment, exception review and final conclusions.
Make the next policy update a focused one
Discuss the technology changes, ownership questions and documentation gaps you need to address.