Diagnostic Architecture
Ten disciplines, one adoption path.
Capability Scale
5 Maturity Levels
01
02
03
05
Level 1: Unprepared
Level 2: Initiating
Level 4: Adopting
Level 5: Scaling
AI awareness is restricted to select groups. Processes require heavy manual intervention. Significant barriers to AI Adoption exist.
AI capabilities become deeply embedded into business strategy, automated workflows, organizational culture, and continuous process optimization.
Limited AI awareness, ad-hoc experimentation, unvetted tool adoption, and severe data quality barriers across operational units.
04
Level 3: Developing
Initial process standardization begins, foundational data pipelines take shape, and structured governance frameworks enter active deployment.
Robust infrastructure, clear ROI metrics, high data trust, and scalable integration protocols enable confident enterprise deployment.
Evaluation Criteria
20% Total Weight
Strategy and Leadership Alignment
Evaluates executive literacy, decision speed, and business value alignment. Ensures AI initiatives address strategic bottlenecks rather than speculative tech experiments.
Process Discipline and Data Trust
Grounded in Lean Six Sigma principles to eliminate process waste prior to automation. Assesses data completeness, lineage, and master data governance across core operations.
Technology Architecture and Workforce Skills
Audits cloud readiness, API integration density, and security posture alongside workforce prompt literacy, cross-functional agility, and internal champion density.
Governance, Use-Case Risk, and Adoption
Establishes responsible AI guardrails, model risk management, and structured change management protocols to guarantee long-term workforce utilization.
Make readiness your competitive advantage
Benchmark where your organization stands today—and what it will take to move confidently into AI adoption.