FR EN
AEES

AEES Executive Certificate in Generative AI and enterprise decision

Judge an AI output, protect the file and own what goes to the client. This AEES certification attests generative AI and enterprise decision.

  • AssessmentProfessional assessment
  • Attempts2
  • PreparationIncluded
  • France
  • Canada
Description

Generative AI and enterprise decision

A vague familiarity with “Generative AI and enterprise decision” is no longer enough. This belongs with AI, data and digital. You lead AI, you govern data and you frame a digital change. People are hired to decide, not just to name the topic. This AEES certification is for professionals, managers and leaders who want to judge an AI output, protect a confidential file and decide human oversight. No diploma is required. What is required is a working command of written French, and the will to show the subject on a real file, in a company, a public body or a partner organisation.

You are not joining a long degree. You take “Generative AI and enterprise decision” seriously enough to use it, and seriously enough for someone else to read it on a file. Everything happens online, around a job you already have. You prepare if you need to, then you sit a professional assessment. The AEES Executive Certificate, if it is issued, is proof in your name, and it can be checked. It holds in a CV, a move or a cooperation. It is a short specialisation, issued by a higher-education institution. You see at once what you are buying: a targeted title, not a course catalogue.

Afterwards you can carry “Generative AI and enterprise decision” into a team, a file or a new responsibility, and explain your choices to a manager, a funder or a partner institution. Others will see that you can judge an AI output, protect a confidential file and decide human oversight, including outside your own organisation. If you succeed, AEES issues an AEES Executive Certificate in your name, with a unique serial number that can be checked in the public register. The award stays in your workspace. It shows a professional judgement you have demonstrated, useful for a CV, a new post or work in common.

Skills

What this certificate attests

The capabilities the assessment attests if you pass.

  • Judge an AI output
  • Protect a confidential file
  • Decide human oversight
  • Keep a human accountable for what is sent
  • Document the use of AI when the context requires it
  • Decide what you say when an output has already circulated
ESCO classification — European Skills, Competences, Qualifications and Occupations

ESCO, the European skills vocabulary

This is the European Commission’s classification of skills, competences, qualifications and occupations. This certificate is linked to it through the skills below. Each link opens the official record.

Knowledge & research

Related scientific readings

Scientific readings related to this certificate.

Preparation included

To prepare for the assessment

After purchase, a preparatory course is available: 6 written modules, without an instructor, at your own pace. You are not required to follow it before opening the assessment. Each module sets out the notions, a commented case, the points to keep and a FAQ. It covers Use, Confidentiality, Quality and Oversight.

When you are ready, you enter the assessment: a file already open, incomplete facts, conflicting views. You move through successive decisions. This is not a full taught programme with pedagogical supervision.

Structured written course

Notions, objectives and concrete examples, organised progressively.

Applied case

A commented professional situation to anchor the theory.

FAQ and preparation

Frequent doubts, then questions to go further on your own.

  1. Module 1: Use. Decide what the tool is allowed to see Generative AI can read, transform, and produce text, images, code, and summaries in seconds. The same ability that makes it helpful also makes it risky: anything you show to a model can be logged, retained, or learned from depending on the tool and configuration. In this module, you will learn how to decide what the tool is allowed to see, and how to make that decision traceable, consistent, and defensible in a real enterprise setting. The first move is not technical. It is a framing decision: what problem are you solving, and what minimum information is needed for the model to do that job? From there, you will select the right workspace, prepare inputs, decide the access pattern, and define human oversight. You will balance speed and quality with risk exposure, and you will document what you chose and why.
  2. Module 2: Confidentiality in Generative AI for Enterprise Decision Generative AI can accelerate analysis, drafting, and decision support, but a single paste into a public chatbot can move a confidential file outside your organisation’s control in seconds. This module teaches you how to stop that paste, how to work safely when AI is useful, and how to keep a clear record of what was sent and why. Confidentiality here means controlling who can see and use information. It covers business secrets, client documents, security details, and personal data that your organisation has committed to protect. Compared with email or cloud drives, generative AI introduces new exposure points. A user might paste a document into a web form, connect a collaboration tool to an external model, or accept a model’s request to fetch a file. The risks include disclosure to a third party, retention by a vendor, model outputs that echo sensitive content, and loss of auditability.
  3. Module 3: Quality, Read a fluent output as a draft, not as a fact Generative models write convincingly. That is their strength and your risk. In business, fluency can mask gaps in grounding, math, sources, or relevance. This module builds a practical discipline: you will treat every model output as a draft, test it against decision needs, and either repair it or set it aside. The standard is simple. If you would not sign your name under the sentence, you should not let the model sign for you. You will work with a minimal set of controls that fit a busy day. You will triage by materiality, verify a sample rather than every line, and document only what is necessary to defend the outcome. You will ask adversarial questions, run quick numeral checks, and seek explicit references when the decision depends on external facts. When there is no safe shortcut, you will escalate to a human expert and record that handover.
  4. Oversight: Keeping a human accountable for what is sent Generative AI can draft, summarize, translate, and propose options at a speed no team can match. That speed is useful only if your organization knows who is responsible for what gets sent. Oversight ensures there is a person who understands the stakes, checks the output, and accepts accountability for its accuracy, appropriateness, and timing. Oversight is not about mistrusting technology. It is a discipline that protects customers, colleagues, and the enterprise by placing a human judgment layer before an AI-assisted action. In practice, this means mapping which decisions need review, defining who signs off, and documenting how the decision was reached. Without that clarity, small errors can scale fast, and good work can be undermined by a single unvetted claim or leak.
  5. Trace This module focuses on a practical ability: tracing how you used generative AI in work that matters. You will learn when a trace is required, what to capture without drowning in paperwork, and how to store and communicate that trace to colleagues, auditors, or clients. The goal is a repeatable habit that protects you and your organization while keeping delivery fast. Tracing is not an academic exercise. It connects to core professional duties such as transparency to clients, compliance with data protection rules, and model risk management. In some settings, it is a legal or contractual expectation. In others, it is simply the right thing to do because a decision will have significant effects on people or the business, and it must stand up to review.
  6. Module 6/6, Client: Responding when an AI output has already circulated By this point in the certificate you have assessed quality, protected confidential inputs, organized human oversight, and kept trace. This final module covers the moment that feels the hardest in practice. Something generated by AI has left your control. People have read it, maybe forwarded it. Some facts are wrong, some names should not be there, or the tone misrepresents your client. You cannot pull it back from every inbox or feed, so you must choose your response with discipline. This is a client decision. It blends risk, law, communications, and operations. The first trap is to improvise messaging while you are still guessing about the exposure. The second trap is to wait for perfect knowledge and let rumors set. Your method must do both at once. Contain and learn fast while you get a minimal, accurate statement out to the right audiences.