AI Architecture Audit
A structured evaluation of where AI fits in your organization, what should be automated, and where human oversight is mandatory.
Why an audit comes first
Most AI initiatives fail because automation is applied too early, in the wrong place, or without controls.
The AI Architecture Audit prevents wasted spend by determining:
- Which workflows are safe to automate
- Which require human-in-the-loop oversight
- What data is usable — and what is not
- Where AI would introduce unacceptable risk
This audit is not for
- Buying AI tools “just to try them”
- Replacing judgment-heavy roles
- Deploying black-box automation
- Skipping governance and controls
What we evaluate
Workflows
Repetitive tasks, handoffs, delays, and failure points.
Data readiness
Data quality, access, structure, and isolation constraints.
Risk & governance
Where automation must stop, escalate, or be reviewed.
Economic impact
Labor cost recovery, throughput gains, and ROI.
Tooling landscape
Existing systems, integrations, and constraints.
Deployment strategy
Phased rollout plan with control points.
How the audit works
Discovery
We review your workflows, tools, and objectives.
Feasibility mapping
Tasks are categorized by automation safety and complexity.
Architecture outline
We define where AI fits — and where it does not.
Recommendations
You receive a clear decision framework and next steps.
What you receive
- Workflow automation map
- Risk & governance boundaries
- AI feasibility assessment
- Phased deployment roadmap
- Clear recommendation: proceed or pause
Outcome guarantee
You will leave knowing whether AI is worth pursuing — and exactly why.