Build · Deploy · Assure
Production AI Readiness Assessment
A rigorous evaluation of your organization's readiness to move AI from experimentation to production.
Operating method
- 01
Build
Scope and construct the workflow
- 02
Deploy
Install it in real operations
- 03
Assure
Prove it keeps working
Why readiness matters.
Most organizations have AI pilots. Few have the operating model to deploy them. The gap between a successful experiment and a production-grade AI system is not technical — it is operational, organizational, and regulatory. This assessment closes the gap.
87%
of AI projects never reach production
4-8
weeks to complete the assessment
30/60/90
day roadmap delivered at conclusion
What We Assess
Six domains of readiness, evaluated against the operational and regulatory requirements of production AI.
Governance Maturity
Evaluate existing AI policies, review processes, decision rights, and accountability structures against the requirements of production deployment.
Data Readiness
Assess data quality, lineage, access controls, and pipeline reliability to determine whether your data infrastructure supports production AI.
Infrastructure & Security
Review compute, deployment pipelines, monitoring capabilities, and security posture for production-grade AI workloads.
Risk Posture
Map AI-specific risks across use cases, including bias, drift, adversarial exposure, and operational failure modes.
Workforce Capability
Evaluate organizational readiness — from technical teams to executive leadership — to operate, maintain, and govern AI systems in production.
Compliance Alignment
Map current AI practices against applicable regulatory frameworks including NIST AI RMF, EU AI Act, ISO 42001, and industry-specific standards.
Deliverables
Every assessment produces a comprehensive set of operational artifacts — not a slide deck.
Production AI Readiness Assessment
Contact for pricing
A rigorous assessment of your organization's readiness to deploy AI into production environments. Covers governance, data, infrastructure, risk, and workforce readiness.
- 01AI use case inventory and classification
- 02Risk tiering across all active and planned AI systems
- 03Ownership map with clear accountability assignments
- 04Governance gap assessment against production requirements
- 05Evaluation and readiness criteria for each use case
- 06Evidence requirements for compliance and audit readiness
- 0730/60/90-day remediation and deployment roadmap
- 08Executive briefing with findings, risks, and recommendations
Timeline
Week 1-2
Discovery
Stakeholder interviews, document review, AI inventory
Week 2-4
Assessment
Domain evaluation, risk analysis, compliance mapping
Week 4-6
Analysis
Findings synthesis, roadmap development, evidence mapping
Week 6-8
Delivery
Executive briefing, deliverable handoff, roadmap review
Total engagement duration: 4-8 weeks depending on organizational complexity and number of AI use cases under review.
Next step
Understand where you stand before you deploy.
Schedule a confidential conversation about your AI deployment landscape, regulatory requirements, and organizational readiness.
Schedule an AI Readiness CallRequest an Assessment
Provide details about your organization and AI landscape. We will follow up within one business day.