Executive Briefing — AI Implementation Risk
Typical failure multiplier
3–5×
of annual tool investment
Organizations at the $15M–$75M scale are committing to AI platforms at an accelerating rate. Most are doing so without a structured readiness assessment. The typical result: the tool underperforms, the team absorbs the gap manually, and the cost of recovery runs 3 to 5 times the original annual contract value.
Illustrative exposure model
ILLUSTRATIVE — based on a $60K/yr contract at the 3–5× multiplier range.
Scale linearly against your actual contract value. Multiplier increases when
multiple readiness conditions are absent simultaneously.
What standard vendor evaluation does not surface
Five conditions that determine whether the investment succeeds — and what each gap costs
The Process Illusion
The process isn't documented consistently. AI automates the variation, not the workflow. Output becomes unreliable immediately — and the team absorbs the gap manually.
0.4–0.8×
of contract / yr
The Ownership Gap
No named person owns output quality. Errors propagate until they reach a customer or a decision. Recovery requires tracing every affected output — retroactively.
0.5–1.0×
of contract / incident
The Data Mirage
Data exists but isn't clean, consistent, or governed. The AI learns from the errors and produces wrong output systematically — not occasionally.
0.6–1.2×
of contract / yr
The Hidden Price Tag
The platform fee is the smallest number. Labor to manage it, integration costs, and exception handling are where the budget actually breaks — and they aren't in the vendor's proposal.
1.5–2.5×
of contract / yr
The Fine Print Risk
Data handling terms, training rights clauses, and liability limitations were agreed to without review. Exposure compounds when regulated data or client confidentiality is involved.
variable
legal + reputational
$500
90-min working session
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