When AI is added to a workflow, it is easy to lose track of who is responsible for each decision. That is the part most often missed.
Every system we design answers four questions in writing before anything goes live.
1. What may AI do?
AI is very good at research, sorting, summaries, drafts, recommendations, routing and monitoring. It can also carry out low-risk actions within defined rules, for example creating a task or tagging a record.
The key words are “within defined rules”. An AI agent should have the narrowest permissions that let it do its job, and nothing more.
2. What must a person approve?
Some decisions carry commercial, legal or human weight. In our systems, a person approves:
- Pricing exceptions, discounts and high-value commitments
- Hiring decisions and anything that affects a person’s livelihood
- Legal, compliance-sensitive or regulated content
- Strategic changes, such as new rules for an agent
- Sensitive communications, such as complaints or refunds
The approval point is drawn on every workflow diagram, so everyone can see it.
3. What does the system log?
Where it is technically appropriate, the system records inputs, outputs, decision points, exceptions, approvals and outcomes. Logs make it possible to answer “why did this happen?” and to improve the system with evidence.
4. How does it fail safely?
Every system has a plan for when something goes wrong: escalation paths, retries, fallback processes and a manual override. These are designed and tested before going live, not added after the first incident.
- AI ACTIONAI drafts and recommendsWithin rules.
- EXCEPTIONRule checkUnsure cases stop.
- HUMAN APPROVALPerson approvesNamed owner.
- AUTOMATIONSystem executesAllowed actions only.
- DATAEverything loggedReady for review.
A shared language for every diagram
Every CONSULIGENCE workflow diagram uses the same six-part legend: AI ACTION, AUTOMATION, DATA, HUMAN APPROVAL, KPI and EXCEPTION. A leader can look at any diagram and see, at a glance, where people stay in control.
Governance is not a brake on AI. It is what makes it safe to use AI in the work that matters.
A simple test
For any AI workflow in your business, ask: if this step went wrong, who would know, how quickly, and who would put it right? If the answer is unclear, the workflow needs an approval point, a log or a fallback before it needs more automation.
