Conventional automation
When the rule is stable.
Calculating, moving, notifying or checking an explicit condition does not require a probabilistic model.
My workSupervised
Automation and applied AI
Useful AI also knows when to stop.
I design systems that assist with a specific task, show their sources and return ambiguous cases to the people responsible for decisions.
Evaluation chamber
Case observed in real time
Authorised input
Incoming message + business rules
Task
Extract the need, identify missing information and suggest the next action.
Proposed result
Structured enquiry, three fields to confirm before assignment.
Quality signal
Medium confidence
Decision
Human approval required
The first decision
Do you actually need AI?
Applied AI
When language resists rules.
Reading, matching, summarising or recommending may justify AI if quality remains measurable and controlled.
Safeguards
Source.
Measure.
Supervise.
Authorised sources
The system knows where to search, what it may use and what it must not expose.
Observable quality
Tests cover real cases, expected errors and the limits of the result.
Human handover
An ambiguous case must be easy to flag, pass on and correct without blocking the process.
Suitable situations
Start with a specific task.
Technology follows an understanding of the process, data and acceptable level of risk.
Qualify
Read an enquiry, identify its intent and flag information to request before assigning it.
Find
Search internal documentation and produce an answer linked to verifiable passages.
Assist
Prepare a decision or action while letting the operator understand and correct it.
Supervise
Observe results, detect drift and improve rules using real cases.
My contribution
From the use case to a supervised system.
Use-case scoping
Assess expected value, data, risks and simpler alternatives.
Assisted or automated workflow
Coordinate stages, tools and human approvals around a specific task.
Integrated AI interface
An assistant, semantic search or specialised agent within the working environment.
Evaluation and supervision
Test sets, traces, confidence thresholds and recovery procedures when the system is uncertain.
Useful questions
What to know before deciding.
Can every process be automated with AI?
No. Stable, deterministic tasks often benefit from conventional rules. AI becomes relevant when work involves language, search or decisions that are hard to formalise fully.
How do we keep control over responses?
The system is designed with identifiable sources, action limits, human approvals and tests suited to the risk level of the use case.
Can we start without a major transformation project?
Yes. An initial scope can target one specific, measurable task and expand only if observed results justify it.
Your project