Work · organizations
Real work first. AI in the gesture.
For a leadership team, a prevention team or an SME: observe the activity — DUERP, MSDs, tools, agents — and decide what to frame, integrate or refuse before investing.
Activity ergonomist since 2020 — field work, not AI consulting. AI lead · CPM Réunion. Three lines are enough: situation, decision, constraint.
Diagnosis
What wears work down.
A compliant DUERP can still be unusable. Activity diagnosis connects the signals — DUERP, MSDs / psychosocial risks, QVCT, absenteeism — to the situations where risk actually appears, so the first change is defensible.
- Start from the field signal, not the document alone
- Work situations: gestures, pace, tools, compensations
- Prioritized actions — not a report that gathers dust
Situated AI
What AI changes in the activity.
Same field file: find where AI already acts, frame responsibility and supervision, integrate one component into the work loop — without stacking tools or promises.
- Start from real activity, not from the tool
- Connect agent → responsibility → supervision
- Decide what gets delegated and what stays under human control
Training
Build skill before investing.
Individuals, managers and teams: understand what AI moves in cognition, attention and skill — so they can decide what to delegate before buying a tool. Anti-atrophy, not one more training.
- Start from real gestures and decisions, not from slides
- Connect usage, supervision and responsibility
- Decide before investing — not after
In the field
DUERP, MSDs, mental load, tools — the signals the activity makes legible.
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DUERP & prevention
Bring the document back to real work — not compliance alone.
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MSDs / psychosocial risks
Read the constraint at the workstation, not only the symptom.
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QVCT & mental load
Work situations: pace, disruptions, multiple screens.
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Absenteeism
Recover the signal inside the activity, not just treat the curve.
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Tools & process
Double entry, ERP friction, AI already present without a frame.
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AI or agent project
Integrate it into the loop — supervised, not stacked on top.
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Work situations
Gestures, workstations, rotations, observable compensations.
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Cognition & attention
What AI moves — skill, vigilance, errors.
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Supervision & responsibility
Who validates, who takes back control, what gets refused.
Method
Observe · Decide · Measure.
One loop before investing — the same field discipline.
Observe
Real work in the field: gestures, workstations, where AI is already entering without a decision. Make the activity observable — not one more report.
Decide
Delegate, keep human, refuse. Nothing leaves without validation — responsibility and supervision are written down.
Measure
Cognition, attention, skill, errors — on the activity, not on the demo. Keep it if the work changes; stop it if it does not.
FAQ
Common questions.
What is an activity ergonomist?
An activity ergonomist analyses real work — what people actually do, not what the job description says. Julien Talbot is an activity ergonomist based in Réunion (France): work diagnosis (DUERP, MSDs, psychosocial risks), situated AI integration and team training.
Do you work outside Réunion?
Yes. Julien Talbot is based in Réunion and works across the island in person. Missions in mainland France or remotely are scoped case by case, combining video calls with grouped observation time.
How does an engagement start?
Three lines by email are enough: the situation, the decision at stake, the visible constraint. A first conversation picks the right door — diagnosis, situated AI or training — before any commitment.
How is this different from a classic AI consultant?
An AI consultant starts from the tool; an activity ergonomist starts from the work. Julien Talbot observes the activity before recommending what to frame, integrate or refuse, and sells no licences or development — the recommendation stays independent of the solution.
Read
Field cases, in writing
Work together
Three lines are enough.
The situation or case, the decision to make, the constraint already visible. A first exchange to choose the right entry point — diagnosis, situated AI or training.