How ready is your organization to ship AI?

Grounded in the leading enterprise frameworks (Cisco, BCG, AWS, McKinsey), this assessment scores you across six dimensions and places you on a four-tier maturity scale, with concrete next steps. Pick a depth to begin.

What the assessment measures.

Strategy & Value
16%
A clear AI strategy tied to prioritized use cases and measurable outcomes.
Data Readiness
18%
Whether your data is accessible, governed, and ready to ground AI and retrieval (RAG).
Technology & Infrastructure
20%
The platform, evaluation, and observability needed to ship AI to production, not just demos.
Talent & Skills
18%
In-house capability to build and ship production AI, and how you close gaps.
Governance & Responsible AI
12%
Policies and controls for AI-specific risk: hallucination, data leakage, security, compliance.
Adoption & Operating Model
16%
How deeply AI is embedded into real workflows, with leadership backing and change management.

Where you can land.

  • Exploring

    0–25

    AI is on your radar but not yet a built capability. There is interest and maybe some experimentation, but no repeatable path from idea to production. This is a normal and fixable starting point. The fastest move now is one focused, high-value use case taken all the way to a working system.

  • Building

    26–50

    You have pilots and pockets of capability, but getting AI reliably into production is still the bottleneck. Evaluation, data access, and senior engineering are the usual constraints. The priority is turning experiments into systems your business can depend on.

  • Scaling

    51–78

    AI is in production and delivering value in places. The work now is breadth and reliability: more workflows redesigned around AI, stronger evaluation and observability, and the talent capacity to keep pace. This is where focused senior engineering compounds fastest.

  • AI-Native

    79–100

    AI is embedded in how the business runs, with strong data, platform, governance, and talent foundations. The edge now comes from the hardest builds: deeper agentic systems, ambitious tool and MCP integrations, and staying ahead of the frontier. Specialist senior engineers are the multiplier.