How the NATIVE steps connect
Technology projects often raise the same question: we have chosen a tool, but do we know what should change, who will work with it and how we will check the outcome?
The AI-Native Entry Framework starts with that context. N · A · T · I · V · E connects six areas of work. It helps identify what is missing before the next step and builds on practices that already work.
L0 — Navigate: understand the situation
Map current work, AI use and decisions that need to be made. Identify potentially relevant legal questions.
Result: a defined purpose, baseline and priorities. Start with AI.
L1 — Align: agree rules and responsibilities
Define permitted use, data handling, output checks and decision-making. Base the material on actual tools and processes.
Result: rules, responsibilities and an action plan. Prepare company rules.
L2 — Transform: prepare people to work with AI
Develop skills through real tasks. Practise evaluating and correcting results as well as giving AI instructions.
Result: demonstrated skills and usable working practices. People and learning.
L3 — Innovate: make the change work in the team
Create room for practice, sharing experience and evaluating ideas. Agree coordination, capacity and support.
Result: an adoption plan and a way to measure benefits. Team adoption.
L4 — Verify: check readiness and results
Review the intended use, risks and evidence against agreed criteria. Where independent specialist assessment is needed, define its scope and the appropriate expert.
Result: supported findings, open questions and a decision on continuing. Preparing for review.
L5 — Execute: implement and operate
Prepare a brief and acceptance criteria, organise delivery, involve people and assign operational responsibility. Monitor changes and actual benefits.
Result: an accepted solution with the information needed for operation and further development. Choose and implement.
Where to start in your situation
The sequence explains dependencies; it does not require six separate projects. Some activities run in parallel. If you already use AI, begin by understanding use and addressing the most important gaps. If you have tested rules and a prepared team, focus on the specific project. Revisit findings when the purpose, tool or conditions change.