Detailed answer
Key answer: Start with one real AI-enabled workflow where an AI output could become a real-world action. Do not begin with an enterprise-wide transformation.
An organization should begin with one bounded, consequential process. The goal is to see exactly where an AI-generated suggestion becomes something that can affect people, money, machines, infrastructure, contracts, or legal responsibility.
This makes the first step practical: pick a workflow, map the execution point, and decide what must be governed before automation expands.
Step 1: Choose one concrete workflow
A good starting case is narrow enough to inspect, but important enough that a mistaken action would matter. Examples include:
- an AI Agent sending external messages;
- payment, refund, or credit approval;
- supplier or procurement action;
- contract modification;
- account suspension or access changes;
- employee or customer decisions;
- robotic movement;
- energy-system operation;
- infrastructure control;
- use of a high-consequence API or tool.
Step 2: Find where execution begins
The organization should identify the point where the AI output stops being only information and starts becoming an executable action. That point is the first place where LERA governance becomes concrete.
Step 3: Answer five basic questions
- What can the AI propose?
- What can the AI actually cause to happen?
- Where does execution begin?
- Who has authority and responsibility?
- What prevents unacceptable execution?
Many organizations can answer the first two questions, but not the last three. That gap is exactly why a LERA-style execution review is useful.
Step 4: Run a LERA Execution Risk Diagnostic
The recommended first engagement is usually the LERA Execution Risk Diagnostic. It helps the organization:
- define the selected use case;
- inventory AI-generated actions;
- identify the Execution Boundary;
- classify consequence context;
- locate authority and responsibility gaps;
- identify rule and control gaps;
- determine the appropriate next step.
Step 5: Decide the next path
After the diagnostic, the organization may proceed to Execution Boundary Mapping, a Judgment-Governance Blueprint, an Architecture Review, a bounded pilot, or a broader enterprise collaboration.
The objective is not to adopt the name LERA as quickly as possible. The objective is to know whether the organization’s AI system can act before the organization has defined who may permit that action, under which rules, with whose responsibility, and through which control boundary.
Start with one real execution pathway. Make it visible. Govern it before expanding automation.