Operations & Compliance

Audit preparation and evidence synthesis

Collate and summarise evidence packs for internal and external audits. Identifies gaps against audit criteria before the auditors arrive.

AugmentationPattern-matchingTime savingAccuracy

40–60%

reduction in audit preparation time

Opportunity assessment

Business Impact
2

Minor improvement. Small efficiency gain with limited effect on overall turnover or bottom line.

Feasibility
4

Relatively straightforward. Off-the-shelf tools handle the core task. Implementation is well-understood with good examples to follow.

Data Readiness
3

Moderate data needs. Works with data most businesses hold, but will likely need consolidation, cleaning, or reformatting before use.

Risk Exposure
4

Low risk. Limited external exposure. A human reviews output before it reaches anyone outside the team.

Change Complexity
4

Light people impact. A new tool slots into an existing workflow. Minimal training needed. Most people will adapt quickly.

Tooling required

Standard LLMRAG system

Things to consider

  • Document completeness and accessibility is the main variable — if evidence is scattered across drives, emails, and physical files, the organisation project precedes the AI project.

  • Embed the audit criteria in the RAG system so the AI checks against the actual standard you're being measured against.

  • The time saving in audit prep is significant, but the value only materialises if the audit itself goes better. Track audit outcomes, not just prep time.

  • The most valuable output is a gap analysis — 'here are the criteria we do not have clear evidence for' — rather than a summary of what you do have. Design the AI task around finding gaps, not confirming coverage.

  • Experiment starter: Before the next scheduled internal audit, use an LLM to map available evidence documents against the audit criteria checklist and identify gaps. Have the audit lead validate the gap list. If the AI identifies 80%+ of the gaps the audit lead would have found independently, it earns its place as a first-pass tool.

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