Measure where your organization and its people stand on the AI adoption journey, and know your next step — across clear levels, assessment dimensions, and a practical roadmap.
An index that measures your organization's AI maturity across five levels — from AI-Ready to Autonomous Enterprise — pinpointing where you stand and charting your roadmap to the next level across six strategic dimensions.
Infrastructure, data, and leadership awareness are in place, but AI use is still experimental and scattered across proof-of-concept initiatives, without systematic adoption or clear enterprise return.
AI tools are adopted across several departments and deliver measurable productivity gains, but core processes are still designed human-first, with AI as an assistive layer rather than a design center.
AI is a core part of process design under an "AI-by-default" policy; core processes have been redesigned around it, and decisions are driven by data and models.
A network of collaborating AI agents executes large parts of the work and makes bounded decisions, while humans shift to oversight roles (Human-on-the-Loop).
A large share of operations runs autonomously (Zero-Touch) via a network of agents and automation, with humans in a strategic supervisory role. A rare and aspirational level.
An index that measures your personal AI maturity across four levels — from AI User to Agent Manager — clarifying your skills and charting your growth path.
Uses AI tools occasionally for isolated tasks, with basic usage and prompting skills.
Backed by a set of AI tools that continuously boost productivity and are woven into daily workflow.
Starts every task by considering how AI can execute or accelerate it before doing it manually, and automates repetitive work.
Manages a team of AI agents: delegates tasks, reviews results, and intervenes when needed rather than doing all the work personally.
AI vision, executive sponsorship, budget, and goal alignment
Data quality and availability, platforms, integration, and technical security
Models, copilots, agent systems, and AgentOps practices
Employee skills, adoption rate, and an AI-by-default culture
Process automation, human–AI collaboration, and oversight patterns
Policies, compliance, risk management, and responsible use
Tool variety, usage skill, and prompting
Applying AI-by-default in daily tasks
Task automation, building and directing agents
Reviewing outputs, quality assurance, and ethics
Practical steps to advance from each level to the next.
Measure your organization and your team in one track, and get a single unified report with the full picture — at one scalable price.