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Why 80% of Enterprise

AI Projects Fail Before They Start

Most AI projects do not fail because of bad technology. They fail because the organization was not ready. Your client’s team evaluated a dozen tools last year. None of them connected to existing systems. They ran two pilots that looked promising for eight weeks, then stalled when nobody could explain how the data would flow. And somewhere in the last quarter, a competitor moved faster. Not because the competitor had better AI. Because the competitor figured out where to start.

An AI readiness assessment eliminates this pattern. It maps the entire organization’s operations, scores readiness across five pillars, and identifies the specific workflows where AI will deliver measurable returns. The output is not a slide deck with vague recommendations. It is a costed, prioritized roadmap your agency can sell implementation against.

80%

of AI projects fail to reach production

RAND Corporation research found AI projects fail at twice the rate of non-AI IT projects, primarily due to organizational readiness gaps.

4%

have enterprise-wide AI capabilities

BCG found that only 4% of companies have achieved scaled, enterprise-wide AI deployment. The remaining 96% are stuck in pilots or planning.

52%

of organizations lack AI talent and skills

The talent gap is the most commonly cited barrier to AI adoption. Readiness assessments identify exactly which skills are missing and where.

85%

cite data quality as top AI challenge

KPMG found that data quality, accessibility, and governance are the number-one blocker to AI success. No amount of tooling fixes bad data foundations.

What Is an

AI Readiness Assessment and Why Your Clients Need One

An AI readiness assessment is a structured evaluation of an organization’s ability to successfully adopt and implement artificial intelligence. It measures capabilities across five pillars — data, infrastructure, people, process, and governance — to identify where AI will deliver value, where it will not, and what needs to change before implementation begins.

Unlike a maturity model that scores where you are on a scale, a readiness assessment answers a more urgent question: can you actually start, and if not, what is blocking you? The output is not a benchmarking report. It is a prioritized, costed roadmap with implementation-ready projects your agency can sell.

For agencies, this is the highest-leverage service you can offer. Every assessment generates three to five follow-on implementation projects. It is your entry point into the AI conversation with any client.

How It Compares

Dimension AI Readiness Assessment AI Maturity Model Generic Consulting Audit
Focus Can you start? What is blocking you? Where are you on a scale? General operational review
Output Prioritized roadmap with costed projects Maturity score and benchmarks Recommendations report
Timeline 8–12 weeks 2–4 weeks 6–12 months
Actionability Implementation-ready projects Strategic planning input Advisory only
Agency Revenue 3–5 follow-on projects Retainer consulting Unclear path

The Five Pillars of Enterprise

AI Readiness

Every organization’s AI readiness is determined by five interdependent pillars. If even one is weak, it undermines progress across all others. We score each pillar on a 1–5 scale, identify specific gaps, and map the path from current state to implementation-ready.

1
Data Foundations

Quality, accessibility, governance, integration across silos. We assess data completeness, freshness, standardization, and whether it can actually feed AI models.

85% of leaders cite data quality as their top AI challenge — KPMG

2
Infrastructure and Architecture

Compute capacity, cloud readiness, API ecosystem, security posture, and scalability. Can the existing architecture support AI workloads without a full rebuild?

We map every integration point and identify what connects, what breaks, and what is missing

3
People and Skills

AI literacy across the organization, data science talent availability, executive sponsorship strength, and change management readiness.

52% of organizations say they lack the talent to execute AI initiatives — OvalEdge 2026

4
Process and Workflow

Which business processes are automatable, what is the current state of each, where are the bottlenecks, and which ones will deliver the fastest return?

We evaluate 42 assessment areas across seven departments to build a complete picture

5
Governance and Ethics

Policies, compliance posture (EU AI Act, CCPA, HIPAA), risk management frameworks, decision-making structures, and responsible AI guidelines.

Governance is now the fastest-growing pillar as regulatory scrutiny intensifies globally

We do not deliver a surface-level review. Every assessment covers seven core departments with six assessment areas each, evaluating the specific workflows, tools, data flows, and integration points that determine where AI will work and where it will not.

Sales

Lead scoring, pipeline acceleration, forecast modeling, CRM enrichment, conversation intelligence, and deal-stage automation.

Marketing

Campaign automation, audience segmentation, content optimization, email personalization, demand generation workflows, and attribution modeling.

Operations

Workflow automation, resource allocation, inventory management, quality control, scheduling optimization, and supply chain intelligence.

Finance

Expense categorization, invoice processing, fraud detection, financial forecasting, accounts payable automation, and compliance reporting.

Customer Support

Ticket routing, knowledge base automation, sentiment analysis, self-service portals, response generation, and escalation prediction.

Human Resources

Resume screening, onboarding automation, retention prediction, compliance tracking, performance analysis, and workforce planning.

IT and Engineering

Infrastructure assessment, security posture evaluation, code review automation, DevOps optimization, API readiness, and system integration mapping.
Weeks 1–2

Discovery and Scoping

Stakeholder alignment sessions. Scope confirmation across departments. System access setup and initial documentation review. We define what success looks like before we start measuring.

Week 3–5

Department Deep Dives

Four to six interviews per department. Direct access to CRM, ERP, project tools, databases, and data warehouses. We see integration maps, data quality issues, isolated systems, and what actually flows between them.

Week 6–7

Analysis and Scoring

Score each of the five pillars on a 1–5 scale. Identify quick wins versus long-term strategic plays. Build the opportunity matrix that maps every finding to estimated effort and expected return.

Week 8–9

Roadmap Construction

Prioritize opportunities by ROI and implementation effort. Estimate costs and timelines for each project. Map dependencies and prerequisites. Build the phased implementation plan your agency can sell.

Week 10

Possibilities Report Delivery

Executive presentation. Department-by-department findings. The complete Possibilities Report with every opportunity mapped, effort estimated, and revenue potential calculated. Your agency delivers it. We stay behind the curtain.

What Is Included in the

Possibilities Report

This is not a slide deck with vague recommendations. The Possibilities Report is a detailed, costed, prioritized roadmap that gives your client clarity and gives your agency a pipeline of implementation projects.

Every finding is mapped to a specific action. Every action has an effort estimate and an expected return. Your client sees exactly what to do, in what order, and what it will cost. Your agency sees three to five projects ready to scope and sell.

Report Deliverables

1

Executive Summary

Two-page overview designed for C-suite stakeholders who need the strategic picture without the technical detail.
2

AI Readiness Scorecard

All five pillars scored 1–5 with detailed findings, gap analysis, and recommended actions for each.
3

Department-by-Department Findings

Seven department sections with 42 assessment areas. Current state, identified opportunities, and recommended automations for each.
4

Opportunity Matrix

Every opportunity classified as quick win, medium-term project, or long-term strategic investment. Ranked by ROI and effort.
5

Implementation Roadmap

Phased plan with dependencies, prerequisites, cost estimates, and timelines for every recommended project.
6

Risk Register

Technical, organizational, and compliance risks identified during the assessment. Mitigation strategies for each.
7

90-Day Quick-Start Plan

The three highest-impact, lowest-effort projects that can begin immediately after the report is delivered.

How Much Does an

AI Readiness Assessment Cost

This is the most profitable service an agency can add to its portfolio. Unlike ongoing retainers where margins compress over time, an AI readiness assessment is a fixed-scope, high-margin engagement with a clear deliverable and a built-in upsell path.

Every assessment we have delivered has generated between three and five follow-on implementation projects worth three to eight times the assessment fee. The client gets a roadmap they trust because it came from your team. You get a pipeline of pre-sold projects backed by data the client already approved.

You set the price to your client. We charge a wholesale rate. The margin is yours to keep.

Every assessment generates on average 3-5 implementation projects worth 3-8x the assessment fee. This is not a cost center. It is your most efficient sales tool.

Focused Assessment

$15,000 – $30,000

Ideal for agencies testing the model or working with smaller clients. Covers two to three departments within a single business unit with targeted workflow analysis.

2-3 departments

6-8 weeks

Enterprise Assessment

$100,000 – $175,000+

Built for multi-location organizations in regulated industries. Includes vendor evaluation, change management planning, compliance mapping, and executive stakeholder alignment.

Multi-location, regulated

12-16 weeks

Real-World Results After an

AI Readiness Assessment

These are composite examples drawn from actual engagements. The numbers reflect real outcomes. The details have been adjusted to protect client confidentiality.

Operations Department

National Insurance Carrier

Assessment found: 340 hours per month spent on manual claims categorization across three regional offices.

Implemented: AI-powered document classification and automated routing.

Result: 78% reduction in processing time. $420K annual savings. ROI achieved in 4 months.

Knowledge Management

Mid-Market Law Firm

Assessment found: Attorneys spending 12+ hours per week searching for precedent across 15 disconnected databases.

Implemented: RAG-powered knowledge base with natural language search.

Result: Research time cut by 65%. Junior attorney productivity up 40%.

Customer Support

B2B SaaS Company

Assessment found: 62% of support tickets were repetitive questions already answered in existing documentation.

Implemented: AI chatbot with knowledge base integration and escalation routing.

Result: 48% ticket deflection in 60 days. CSAT improved from 3.8 to 4.4.

Hr / Compliance

Regional Healthcare Network

Assessment found: Credentialing process took 45 days with 23 manual handoffs across departments.

Implemented: Automated credential verification and compliance tracking system.

Result: Credentialing reduced to 12 days. Compliance violations dropped 91%.

Industries Where AI Readiness Assessments

Deliver the Highest ROI

AI readiness assessments work across verticals. These four industries consistently produce the highest-value findings because of their data density, regulatory requirements, and process complexity.

Professional Services

Law firms, accounting, consulting. Knowledge is the product. AI turns institutional knowledge into a scalable, searchable asset that compounds in value.

Healthcare

HIPAA-compliant workflows, credentialing, clinical documentation, patient communication. Heavily regulated environments have the highest need for structured assessment.

Financial Services

Compliance documentation, fraud detection, client communication, regulatory reporting. Where the wrong AI decision can trigger regulatory action and reputational damage.

Manufacturing and Logistics

Supply chain optimization, predictive maintenance, quality control, demand forecasting. High-volume, repetitive processes with the clearest automation potential and measurable ROI.

AI Readiness Assessment vs.

Big-Four Consulting Engagement

Agencies typically weigh three options when a client asks for AI guidance. Here is how those options compare across the dimensions that matter.

Dimension WLIQ (White-Label) Big-Four Consultancy DIY / Internal
Cost $40K – $75K $150K – $500K+ “Free” (hidden costs)
Timeline 10 weeks 6-12 months 3-6 months (if completed)
Output Costed roadmap with implementation-ready projects Strategic report with recommendations Spreadsheet with observations
Follow-Through Direct path to implementation (same team builds) Separate implementation vendor needed Internal team stretched thin
Branding Your agency brand, your client relationship Consultancy brand front and center N/A
Implementation Revenue 3-5 projects worth 3-8x assessment fee Separate SOW required No additional revenue

White-Label AI Readiness

Assessment Development for Agencies

The white-label model means your client never knows we exist. You own the relationship, the deliverables carry your brand, and the follow-on revenue stays in your pipeline.

We handle the technical heavy lifting: stakeholder interviews, system audits, data quality analysis, workflow mapping, and report generation. Your team stays focused on client management and business development while we produce the work.

This is the same model we use across all our services. We have been doing white-label development for agencies for over 15 years. The assessment service is simply the newest application of a proven delivery framework.

1

You Scope the Project

We provide technical discovery questions and help you estimate accurately. You position the engagement and close the deal.
2

We Run the Assessment

Our team conducts stakeholder interviews, system audits, and analysis. We operate under your brand. Your client interacts with your team.
3

You Deliver the Report

The Possibilities Report ships under your agency letterhead with your branding. We stay invisible. Your client sees one team: yours.
4

You Sell Implementation

The roadmap feeds directly into projects you can sell. Each assessment generates three to five follow-on engagements. We build those too.

FAQ

What is an AI readiness assessment?

An AI readiness assessment is a structured evaluation of an organization’s ability to successfully adopt and benefit from artificial intelligence. It examines five core pillars: data foundations, infrastructure and architecture, people and skills, processes and workflows, and governance and ethics. The output is a scored report that identifies where AI will deliver measurable ROI, where the organization has gaps that need to be addressed first, and a prioritized implementation roadmap with cost estimates.

An AI maturity model describes where an organization sits on a general adoption curve, typically using labels like Initial, Developing, or Optimizing. An AI readiness assessment goes further by evaluating specific departments, mapping actual workflows, scoring current capabilities against concrete criteria, and producing an implementation-ready roadmap with cost estimates. Maturity models tell you where you are. Readiness assessments tell you exactly what to do next and what it will cost.

A standard full-scope assessment covering all seven departments and 42 assessment areas takes 10 weeks. Focused assessments targeting two to three departments can be completed in six to eight weeks. Enterprise assessments for multi-location organizations or those in heavily regulated industries typically take 12 to 16 weeks to account for additional compliance mapping and stakeholder alignment.

Pricing depends on scope. A focused assessment covering two to three departments ranges from $15,000 to $30,000. A standard full-scope assessment across all seven departments runs $40,000 to $75,000. Enterprise assessments for multi-location or regulated organizations start at $100,000 and can reach $175,000 or more. These are the prices agencies typically charge their end clients. Your wholesale cost through the white-label model is lower.

The standard assessment covers seven departments: Sales and Revenue Operations, Marketing and Content, Operations and Supply Chain, Finance and Accounting, Customer Support, Human Resources, and IT and Engineering. Each department is evaluated across six assessment areas covering data quality, process automation potential, tool readiness, team capability, compliance requirements, and integration complexity. That gives you 42 total assessment areas across the organization.

The Possibilities Report is the primary deliverable. It includes an executive summary with key findings and recommended priorities, an AI readiness scorecard with scores across all five pillars, department-by-department findings for each of the seven areas assessed, an opportunity matrix categorized into quick wins and medium and long-term projects, an implementation roadmap with dependencies and prerequisites, a risk register covering technical and organizational and compliance risks, and a 90-day quick-start plan for immediate action items.

That is one of the most valuable outcomes an assessment can produce. If a client is not ready for AI, the report tells them exactly what needs to change and in what order. This often generates more project work than a green light would. Data cleanup, process standardization, integration work, and training programs are all billable projects that prepare the client for AI while strengthening the agency relationship. Telling a client they are not ready yet, with a clear plan to get there, builds more trust than telling them what they want to hear.

Yes, but access is scoped and temporary. During the assessment we need read-only access to relevant systems to evaluate data quality, integration points, and infrastructure readiness. We work under NDA and can comply with your client’s security requirements including VPN access, SSO authentication, and audit logging. All access is revoked at the end of the engagement. We do not retain any client data after the report is delivered.

Yes. Regulated industries are where assessments deliver the most value because the cost of getting AI wrong is highest. Our assessment framework includes compliance mapping for HIPAA, SOX, GDPR, and industry-specific regulations. The governance and ethics pillar specifically evaluates regulatory readiness, data privacy controls, audit trail requirements, and bias testing protocols. We have delivered assessments for organizations in healthcare, financial services, insurance, and legal sectors.

The Possibilities Report is designed to generate follow-on work. Each recommendation includes scope estimates, effort levels, and expected ROI ranges. Most clients approve two to three projects from the roadmap within 30 days of receiving the report. Your agency presents the implementation proposals. We build the solutions under your brand using the same team that conducted the assessment. This continuity means faster implementation because we already understand the client’s systems and constraints.

You Probably Know

Which Client Needs This First

That client who evaluated 12 tools and implemented none. The one with the AI budget but no AI strategy. The one whose competitor just deployed what they have been talking about for two years.

Send us the details. We will tell you whether an assessment is the right starting point or if there is a faster path to value. No pitch deck. No 90-minute discovery call. Just a direct conversation about whether this makes sense for your client.

Response time: within one business day. Every conversation is covered under NDA. We do not contact your clients directly. Ever.

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