Generative AI Maturity FrameworkAssess your organization's AI readiness

A GenAI maturity assessment evaluates your organization's readiness and capabilities across six key dimensions: Strategy & Leadership, Data & Infrastructure, Use Cases & Applications, Talent & Culture, Governance & Risk, and Agentic AI Systems. It provides a comprehensive view of where you are today and a roadmap for where you need to go.

The assessment is designed for executives, IT leaders, data scientists, and anyone responsible for AI strategy. It's valuable for organizations at any stage of their AI journey, from those just exploring AI possibilities to those with mature AI programs looking to identify improvement areas.

Simply click "Start Assessment" on our homepage. You can begin immediately without creating an account (anonymous mode), or create a free account to unlock additional features like progress saving, industry-specific assessments, and historical tracking.

Basic assessments are free for all users. We offer premium features for enterprise customers including advanced analytics, team assessments, custom branding, and API access. Contact us for enterprise pricing.

Yes! Our platform is fully responsive and works on smartphones, tablets, and desktop computers. Your progress is automatically saved, so you can start on one device and continue on another.

The six dimensions are: (1) Strategy & Leadership - executive sponsorship and strategic alignment, (2) Data & Infrastructure - data quality and platform readiness, (3) Use Cases & Applications - prioritization and deployment of AI use cases, (4) Talent & Culture - workforce skills and organizational mindset, (5) Governance & Risk - policies, compliance, and responsible AI, (6) Agentic AI Systems - autonomous AI capabilities.

Our assessment specifically focuses on Generative AI capabilities and includes the emerging dimension of Agentic AI Systems. It provides actionable recommendations tailored to your industry, benchmarks against peers, and offers a clear roadmap for improvement.

MCP is an open standard for connecting AI models and agents to external tools, data sources, and systems through a common interface. MCP servers expose capabilities (search, filesystem, database access, custom APIs) that any MCP-compatible client can discover and invoke without bespoke integration code. The framework considers adoption of a standardized tool protocol such as MCP a signal of Integrated (Level 4) or higher maturity in the Agentic AI dimension.

Yes — shipping an agent to production without a systematic evaluation harness is treated as a red flag in the framework. Agent evals measure task completion, tool-call correctness, cost, latency, and safety across many runs, and act as a regression gate for every prompt, tool, or model change. Building the eval harness before the agent is a defining practice of leaders.

Reasoning models (extended-thinking variants such as OpenAI o-series and Claude extended thinking) do not by themselves change your maturity level, but how you use them does. Advanced maturity is signaled by using reasoning models selectively for planning-heavy subtasks — while cheaper models handle routine steps in the same pipeline — rather than defaulting to reasoning models for every request.