Applied Assessment NotesReproducible research · FR / EN
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Professional training

AI Training

Professional artificial-intelligence training covering literacy, applied use, control, validation and roadmaps.

A hand filters a cloud of data through a prism, turning it into structured steps that lead to a decision.
From information to decision

Frame, filter, structure and verify before deciding.

Professional practice, not a collection of tricks

Use artificial intelligence without losing control.

Every session begins with the work participants genuinely perform. The aim is not to learn a few spectacular prompts, but to build a working method that protects data, verifies outputs and leaves the decision with an identified person.

Task → authorized data → instruction → output → verification → human decision

Three adaptable programmes

Choose the right level of engagement.

The final content is agreed after a short scoping step covering the audience, current level, authorized tools, data involved and expected outcome.

01

Foundations

Understand, experiment and establish shared rules.

An initial framework for separating useful applications from hype, understanding tool limitations and adopting a verifiable working method.

For whomLeaders, managers and teams seeking a shared foundation.

Available formats
  • Executive briefing — 1.5 hours
  • Team awareness session — half a day
  • In-house training — one day
Intended outcomes
  • shared foundations
  • usage rules
  • first controlled workflows
02

Applied

Work on the team’s real tasks.

A tailored day built around authorized and, where necessary, anonymized cases: documents, analysis, decision preparation or knowledge capture.

For whomBusiness teams, support functions, finance, risk, engineering and education.

Available formats
  • Tailored business-function day
  • Finance, risk or technical day
  • Sector-specific training
Intended outcomes
  • worked use cases
  • reusable templates
  • verification checklist
03

Roadmap programme

Move from experimentation to an organized decision.

An in-depth programme for selecting use cases, defining controls, experimenting with teams and deciding what should—or should not—move forward.

For whomLeadership teams, project teams and organizations preparing a structured initiative.

Available formats
  • Two-day programme
  • AI usage and control assessment
  • Institution-wide programme
Intended outcomes
  • explicit priorities
  • safeguards
  • roadmap and debrief

Modules to combine

Five possible training families.

Modules are combined according to participants’ responsibilities and the applications the organization genuinely wants to examine.

01

AI literacy and usage rules

Understand what artificial-intelligence tools produce and establish shared language before discussing deployment.

  • predictive AI, generative AI, agents and automation
  • hallucinations, bias, obsolescence and fabricated references
  • confidentiality, intellectual property and human accountability
  • internal policy and uses to permit or rule out
02

Operational AI for support functions

Work through a complete process rather than an isolated prompt, with explicit checks before any output is used.

  • research, synthesis and document analysis
  • communications, meeting notes and presentations
  • meeting preparation and reusable templates
  • measurement of time saved and quality achieved
03

AI applied to business functions

Adapt exercises to the language, constraints and documents of the relevant activity without exposing sensitive information.

  • industry, construction and engineering
  • food production, quality and regulation
  • finance, risk and audit
  • human resources, healthcare and education
04

Decision-making, risk and control

Learn when an output can be trusted, how to verify it and when a tool should be corrected or rejected.

  • uncertainty, silent errors and bias
  • validation, sources and traceability
  • use-case selection and expected value
  • human accountability and stopping conditions
05

Assistants, agents and document bases

For more mature organizations: understand the architecture, test access controls and define the evidence required before production use.

  • assistants, agents, application programming interfaces and retrieval-augmented generation
  • connection to internal documentation
  • test sets, access control and operating cost
  • situations in which automation should be avoided

Formats

From a short briefing to a full roadmap.

An engagement can build awareness, provide hands-on practice, specialize a team or prepare a structured initiative.

From 1.5 hours to a tailored engagement

Leadership and management

Executive committees, leaders and managersExecutive briefing, collective workshop or assessment to prioritize initiatives and establish initial rules.

From half a day to two days

Teams and business functions

Cross-functional, business and support teamsAwareness session, standard day, tailored day or specialist training built around concrete tasks.

One day or an in-depth programme

Finance, risk and technical teams

Quantitative, control, audit, engineering and technology teamsFocus on assumptions, uncertainty, validation and the conditions for moving into operational use.

2–3 hours, half a day, one day or an annual programme

Education

Leadership teams, teachers, pupils and studentsTeaching applications, academic integrity, source verification, assessment and intellectual autonomy.

Possible contexts

  • Construction and engineering
  • Industry
  • Food production
  • Finance and risk
  • Support functions
  • Technical training
  • Education

Approach

A use case moves forward only if it survives verification.

Concluding that a tool is unsuitable for a task is not a training failure. It is a useful decision when the reason and the alternative are made explicit.

A person moves through increasingly structured data panels toward a bright opening.
A progressive path

Understand, practise, verify and decide: each stage reduces an identifiable uncertainty.

  1. 01

    Understand

    Frame the audience, authorized tools, tasks, data and expected outcome.

  2. 02

    Experiment

    Work on a real, authorized and, where necessary, anonymized example.

  3. 03

    Verify

    Check the quality, sources, risks, access controls and limitations of the output.

  4. 04

    Decide

    Choose whether to proceed, revise or abandon the use case, with explicit human accountability.

Depending on the selected format

Resources that remain useful after the session.

  • a selection of priority use cases
  • a map of permitted and prohibited data
  • reusable working templates
  • a verification checklist and human-validation rules
  • the situations in which artificial intelligence should not be used
  • depending on the programme, a roadmap and leadership debrief

Shape the training

Start from a concrete problem, not a generic programme.

A short conversation clarifies the audience, constraints and intended outcome before the appropriate format is proposed.

Write to Julien Riposo