CEM · AI

AI Workflow Audit

Assess current AI tool usage across your workflows. Identify Drift Tax exposure. Walk away with a prioritized action plan.

One-time

~1 week

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12–15%

AI False Signal Rate

How often AI claims completion but the output contains errors — the cost driver most teams can't see

Failure Modes Classified

Fabrication, Non-Compliance, Context Loss, Truncation, Overreach, Misdirection

$390K

Sample Annual Drift Tax

20-person team, $75/hr loaded, 5 hrs/week rework — the math most teams haven't done

Methodology validated across 10 production systems · 65 of 69 claims git-auditable

The Engagement

Your team is using AI. But is it producing clean output — or is drift compounding underneath the surface? The AI Workflow Audit answers that question with data. We assess your team's AI-assisted workflows, classify every output against the 6 known failure modes, and quantify what drift is costing you in rework hours and dollars.

You receive an 8–12 page audit report with an executive summary, AI tool inventory, failure mode breakdown with artifact-specific examples, dollar cost estimate, gap analysis, and a prioritized list of what to fix first. The engagement closes with a 30-minute delivery call and a written next-step recommendation within 24 hours.

The assessment methodology was validated across 10 production systems and $75M+ in generated revenue. The benchmark rework rate under CEM is 3.7% — compared to the industry standard of 20–40%.

What You Get

Drift Tax Audit Report (PDF)

8–12 pages covering executive summary, AI tool inventory, failure mode breakdown with artifact-specific examples, cost estimate, gap analysis, and prioritized recommendations.

30-Minute Delivery Call

Findings walkthrough covering top failure modes, dollar cost estimate, and one clear recommended next step.

Follow-Up Recommendation

Written recommendation within 24 hours with the specific next engagement, scope, and what you get.

What Gets Analyzed

Fabrication

Facts, data, citations, or logic that AI invented and can't be verified against source material.

Instruction Non-Compliance

AI ignored part of the prompt, changed scope, or missed explicit constraints you set.

Context Loss

AI lost track of earlier instructions, reversed prior decisions, or treated established context as new.

Data Truncation

AI silently shortened, summarized, or dropped data when the prompt required completeness.

Autonomous Overreach

AI added content, changed structure, or expanded scope without being asked.

Misdirection

AI presented incomplete or wrong output as complete and correct — no signal that something was off.

How It Works

Intake Call

We review your AI environment — which tools, which teams, which workflows, and where rework is showing up. You provide 3–5 AI output artifacts showing prompt, AI output, and final version.

Day 1

Drift Tax Mapping

Every artifact is classified against the 6 failure modes. Each failure instance is logged by type, severity, and estimated rework time. Costs are extrapolated to monthly and annual figures.

Days 2–3