AI Readiness Assessment
Determine whether your organization is ready for AI before buying AI.
AI Quality Depends on Readiness, Not Hype
The HRHK AI Readiness Assessment evaluates whether your organization has the data foundations, infrastructure, governance, security posture, and operational maturity required for successful AI adoption. Rather than starting with AI tools, we start with readiness—because AI amplifies whatever data, security, and governance posture you already have.
Assessment Areas
Data Readiness
Data quality, availability, structure, lineage, governance, and accessibility for AI workloads.
Infrastructure Capability
Compute resources, cloud readiness, API maturity, integration capability, and scalability for AI workloads.
Governance Maturity
Data governance, policy framework, approval processes, audit capability, and compliance readiness.
Security Posture
Data protection, access controls, prompt-injection defenses, agent authorization, and AI-specific security considerations.
Use-Case Evaluation
Identified AI use cases, feasibility assessment, expected value, implementation complexity, and prioritization.
Organizational Readiness
Technical skills, change management, training needs, stakeholder alignment, and cultural readiness for AI adoption.
Assessment Deliverables
Readiness Scorecard
Assessment across all readiness dimensions with maturity ratings and gap analysis.
Use-Case Prioritization
Evaluated AI use cases ranked by feasibility, value, complexity, and risk.
Risk Assessment
AI-specific risks including data exposure, model dependency, governance gaps, and security considerations.
Readiness Roadmap
Phased plan to address readiness gaps and prepare for successful AI adoption.
Move From AI Experiments to Governed AI Infrastructure.
Understand your readiness before investing in AI tools.