AI Implementation Risk — Mid-Market Advisory

Your AI Investment
Isn't Underperforming. It was never set up to succeed.

Organizations between $15M and $75M are committing to AI platforms faster than they're evaluating whether the underlying conditions for success are present. The vendor evaluation doesn't check those conditions. It was never designed to. A structured readiness assessment does — before the recovery cost runs 3 to 5 times your original contract value.

3–5×

Typical recovery cost
vs. annual contract value

5

Conditions the vendor
evaluation doesn't check

$500

Cost of a structured
readiness assessment

First step

AI Readiness
Fit Call

A 20–30 minute conversation. No pitch. No obligation. A direct read on where your current exposure is — and whether a structured diagnostic is the right next move.

Schedule the Fit Call

Vendor-neutral. No tool commissions.
No implementation upsell.

?

The question worth asking before the next budget cycle

If your current AI platform delivered exactly what the vendor's proposal projected, what would that look like in measurable terms right now?

If that answer is difficult to construct, you're not alone. Most organizations at your scale approved the investment based on a vendor-configured demonstration against best-case assumptions. The gap between that demonstration and your actual operating environment is where implementations fail — and it's almost always visible before the commitment is made, if someone is looking for it.

The Five Blind Spots Framework

Five conditions that determine
whether the investment succeeds.

Most AI implementations fail not because the technology is wrong, but because five specific conditions were never evaluated before the commitment was made. Each absent condition carries a measurable cost. All five are invisible to the vendor.

Blind Spot 01

The Process Illusion

The process being automated isn't documented consistently. AI runs the variation, not the workflow. Output becomes unreliable immediately — and the team absorbs the difference manually, invisibly, until it becomes a visible problem.

0.4–0.8×

contract / yr

Blind Spot 02

The Ownership Gap

No named person owns AI output quality. Errors propagate until they reach a customer, a vendor, or a financial decision. Recovery requires tracing every affected output — retroactively, manually, at full labor cost.

0.5–1.0×

contract / incident

Blind Spot 03

The Data Mirage

The data exists but isn't clean, consistent, or governed across systems. The AI learns from the errors and produces wrong output systematically — not occasionally — in the same direction, every time.

0.6–1.2×

contract / yr

Blind Spot 04

The Hidden Price Tag

The platform fee is the smallest number in the total cost of ownership. Staff time to manage the tool, integration remediation, exception handling, and failure recovery aren't in the vendor's proposal — but they're in your budget.

1.5–2.5×

contract / yr

Blind Spot 05

The Fine Print Risk

Data handling terms, model training rights, liability limitations, and compliance implications were agreed to without review. The exposure compounds when regulated data, client confidentiality, or multi-vendor integrations are involved. This is the blind spot most organizations discover last — after it has already created consequences.

variable

legal + reputational

The recovery cost model

When these conditions go unaddressed,
the bill doesn't match the proposal.

Based on a $60,000 annual platform contract: rework and manual remediation runs $80K–$120K. Lost staff productivity during rollout adds $40K–$65K. Integration remediation adds $25K–$50K. Sunk licensing during underperformance adds $15K–$30K. Total recovery cost at the conservative 3–5× multiplier: $180,000–$265,000. Scale linearly against your actual contract value.

3–5×

of annual contract value

The AI Readiness Diagnostic

What a structured
assessment surfaces.

A 90-minute working session against your specific process, data environment, team, and contracts. Not a vendor evaluation. Not a technology audit. A readiness assessment — the one thing the vendor evaluation was never designed to run.

  • Scored assessment across all five conditions Documentation completeness, data risk, team capability, cost reality, and contractual exposure — each evaluated against defined thresholds with a pass, yellow, or fail rating.
  • A clear proceed, delay, or no-go recommendation With the reasoning behind it — not a consultant's opinion, but a structured finding tied to specific, named gaps.
  • A prioritized remediation sequence if gaps are found Which gaps to close first, in what order, and what the re-assessment trigger looks like for each — so delay is structured, not indefinite.
  • A defensible record of the evaluation A scored, documented baseline showing what was assessed, what passed, and what the basis for the recommendation was — before a commitment is made or a budget is approved.

How this differs from what you've already done

Vendor evaluation Configured against demo data in a best-case environment. Assesses whether the tool works — not whether your organization is ready for it.
Internal IT review Evaluates technical integration and security posture. Doesn't assess process documentation, ownership accountability, or data governance at the workflow level.
Pilot deployment Surfaces gaps after commitment is made and budget is spent. The most expensive way to find out the conditions weren't present.
The AI Readiness Diagnostic Evaluates all five conditions before commitment — in 90 minutes, against your specific environment, for $500. Anchored against the 3–5× recovery cost if those conditions are absent.

About Chuck Boyce

30 years of enterprise
implementation experience.

Chuck Boyce founded Cibi Creative to apply the discipline of large-scale systems implementation — the kind developed over 30 years at organizations including IBM and WebMD — to the AI adoption decisions that mid-market organizations are making without the infrastructure enterprise firms take for granted.

Cibi Creative is an independent advisory practice. No tool commissions are earned. The firm's credibility rests on structured honesty — the kind that produces a no-go recommendation when the conditions aren't present, and a proceed recommendation when they are.

30+ years enterprise technology and systems implementation
Former roles at IBM and WebMD
Vendor-neutral — no tool commissions, no implementation upsell
Specialized in AI readiness for organizations without internal advisory infrastructure
Based in Mount Pleasant, SC — serves national clients virtually

Engagement path

Fit Call — Free, 20–30 minutes A direct conversation to confirm scope and determine whether the AI Readiness Diagnostic is the right next step. cibicreative.com/contact
AI Readiness Diagnostic — $500 90-minute working session. Scored assessment across all five blind spots. Proceed, delay, or no-go recommendation with full reasoning.
Single Process Engagement — $2,500 Deep-dive evaluation of one specific workflow. Process mapping, risk identification, and a written implementation brief if the project is viable.
Multi-Process Portfolio Review — $5,500–$6,500 Comprehensive assessment of multiple AI initiatives. Prioritized roadmap with proceed, prepare, defer, and avoid sequencing across all processes.

The right question isn't
whether AI works.
It's whether your organization
was ready for it.

The Fit Call is a 20–30 minute conversation — no presentation, no sales cycle, no obligation. A direct read on where the current exposure is and what the right next step looks like for your specific situation. If the diagnostic isn't the right fit, that's what the call is for.

AI Readiness
Fit Call

Free — 20–30 minutes

A structured conversation to confirm scope and determine whether the AI Readiness Diagnostic is the right next move. Vendor-neutral. No pitch. No commitment required.

Schedule the Fit Call Download the Exposure Summary first →

chuck@cibicreative.com · cibicreative.com
No tool commissions. No implementation upsell. Ever.