Corporate training
Your teams are moving with AI. Build a Responsible AI Practice.
Train your leaders and your teams on their real cases. Informed decisions. Responsible reflexes. Concrete tools.
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Executives · Leaders · Teams
Responsible AI practice
- 7 paths
- For your business challenges
- 20 programs
- Taken alone or as a path
- Your real cases
- At the heart of the exercises
- Concrete tools
- To reuse in your practice
Put together your training in five choices.
Every conversation starts with the same question: what should AI do for your organization?
Your choices have reached us. We will get back to you to build the next steps together.
Choose your path
Training that answers your challenges.
Governing uses, protecting data, assessing an investment or growing skills: start from the decision you need to make. Each program can be taken on its own or as part of a path.
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01
Ensuring a Responsible AI Practice
4 programs
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02
Compliant AI
2 programs
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03
Tracking and understanding AI obligations in HR
2 programs
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04
Sovereign AI
2 programs
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05
AI, the Trojan horse
4 programs
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06
AI for executives
3 programs
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07
AI in augmented selling and communications
3 programs
- Another topic? A question? Write to us
Path 1 · 4 programs
Ensuring a Responsible AI Practice
Build a practice that protects your organization and grows your skills.
Which data should you entrust to AI? Who oversees its results? Which skills should you preserve and develop? Lay the foundations of a responsible practice, then translate them into your organization and your trade.
- Who is it for?
- Executives, managers, professionals and team members who use or oversee AI.
- Prerequisites
- No prerequisites. Open to people discovering AI as well as those already using it.
1.1Ensuring a responsible AI practice
Objectives
Recognize the possibilities, limits and risks of AI in your activities, and the responsibilities that come with using it.
Outcomes
Benchmarks to assess your uses, protect trust and build environmental sobriety into your practice.
1.2Responsible AI practice 102
Objectives
Define roles, human oversight and the mechanisms for explanation, complaint and recourse according to risk.
Outcomes
The foundations of a structured practice, with a responsibility matrix and a roadmap to put it in place.
1.3AI and Law 25
Objectives
Learn to recognize situations that call for a PIA and to govern the personal information used in your AI projects.
Outcomes
A template adapted to AI systems and a PIA started on a real project, to better guide your next decisions.
1.4Securing your future in the age of AI
Objectives
Distinguish the tasks to augment, automate or preserve, while strengthening your judgment and your ability to oversee AI.
Outcomes
A map of your tasks and a twelve-month skills development plan, anchored in your trade.
Tools that stay in your organization
- Self-assessment grid and practice roadmap
- Matrix of roles and human oversight
- PIA template and personal skills development plan
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 2 · 2 programs
Compliant AI
Move from frameworks to the obligations that actually apply to your organization.
Law 25, EU AI Act, OECD, NIST, ISO: which texts apply to you, in what capacity and for which uses? Tell recommendations apart from obligations, then organize their implementation system by system.
- Who is it for?
- Leadership, heads of compliance, privacy, risk and legal affairs.
- Prerequisites
- No legal training required. A basic knowledge of your organization’s obligations helps.
2.1Recommendations and compliance 101
Objectives
Identify the relevant frameworks, tell what is recommended from what is mandatory, and classify your systems by risk level.
Outcomes
A crosswalk table and benchmarks to focus your efforts on the requirements that apply to you.
2.2Obligations and implementation 102
Objectives
Translate the applicable requirements into actions according to your role, your systems and their uses: transparency, oversight, impact assessment and evidence.
Outcomes
A register of obligations by system and a list of evidence to gather, with the gaps to address.
Tools that stay in your organization
- Crosswalk between frameworks
- System classification and register of obligations
- List of required evidence and identified gaps
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 3 · 2 programs
Tracking and understanding AI obligations in HR
Make the most of AI in HR while keeping control of the decisions that affect people.
Résumé screening, interviews, performance reviews, talent management: examine your tools and their effects on people. Learn to protect sensitive information, spot bias and maintain real human oversight.
- Who is it for?
- HR leaders and specialists, recruitment teams, managers, privacy officers and leadership.
- Prerequisites
- No prior technical or legal knowledge required.
3.1Sensitive data, the PIA and Law 25
Objectives
Spot sensitive information in your HR processes and learn to assess privacy issues before adopting an AI tool.
Outcomes
A PIA underway and benchmarks to govern data, its disclosure and automated decisions.
3.2AI-assisted HR, responsible practices and impacts
Objectives
Evaluate an HR tool, recognize its biases and define how to oversee and contest the decisions it influences.
Outcomes
An evaluation grid with a usage recommendation, plus an oversight and contestation protocol.
Tools that stay in your organization
- PIA assessment tool and HR tool evaluation grid
- Assessment of sensitive data, bias and impacts
- Oversight and contestation protocol
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 4 · 2 programs
Sovereign AI
Choose the level of control your organization needs, knowing what it costs.
Where is your data? Whom do you depend on? What happens if your vendor changes its terms or becomes unavailable? Turn your sovereignty intent into selection criteria and deployment decisions.
- Who is it for?
- Leadership, heads of IT, information security, procurement and compliance, especially in sectors where data control is critical.
- Prerequisites
- No in-depth technical knowledge required.
4.1Applied AI sovereignty
Objectives
Define your sovereignty profile, evaluate vendors and identify the clauses to negotiate to better protect your interests.
Outcomes
A vendor grid and concrete criteria to reduce dependency and the risk of lock-in.
4.2Decision-level AI sovereignty
Objectives
Weigh cloud, hybrid or on-premises deployment against control, cost, performance and data sensitivity.
Outcomes
A decision matrix and what to plan for to keep operating if a vendor fails.
Tools that stay in your organization
- Target sovereignty profile
- Vendor evaluation grid and clauses to negotiate
- Deployment model decision matrix
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 5 · 4 programs
AI, the Trojan horse
Know what enters your organization, what AI does there and how to take back control.
A free tool, a feature added to software, an agent acting on the team’s behalf: AI comes in through many doors. Learn to inventory uses, understand systems, measure their results and react when they exceed the limits you set.
- Who is it for?
- Leadership, board members, heads of risk, IT, security, compliance and operations, and AI project leads.
- Prerequisites
- Familiarity with risk management helps but is not required.
5.1Keep AI under control
Objectives
Take inventory of uses, including shadow AI, define your risk tolerance and assign responsibilities.
Outcomes
An inventory and the foundations of a governance charter, to know who uses what, with which data and under what oversight.
5.2Inspect the gift · Map
Objectives
Describe the purpose, context, data, third-party components and limits of an AI system.
Outcomes
A mapping sheet that makes benefits, dependencies and possible impacts visible before you decide.
5.3Transparency and alignment · Measure
Objectives
Choose the metrics, tests and acceptance thresholds to evaluate a system’s results, biases and alignment.
Outcomes
An evaluation plan to check what AI produces, track its deviations and document what remains uncertain.
5.4Minimize AI risks
Objectives
Assess the risks of models, automations and agents throughout their life cycle, then link each risk to a decision.
Outcomes
Risk tolerance and decision tools, and a shutdown plan put to the test through simulations.
Tools that stay in your organization
- Inventory, mapping sheet and governance charter
- Evaluation plan and risk tolerance and decision tools
- Stress-test scenario and documented shutdown plan
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 6 · 3 programs
AI for executives
Invest where AI creates value and demand the information you need to steer it well.
Which projects deserve your budget? What do integration, oversight and errors cost? When do you move from pilot to deployment? Tie your AI choices to the organization’s priorities and to traceable decision criteria.
- Who is it for?
- Executives, SME owners, leadership teams, boards of directors, finance leaders and heads of operations or AI investment.
- Prerequisites
- No technical AI knowledge required.
6.1Owning AI 101
Objectives
Spot where AI can create measurable value and prioritize use cases by value, feasibility and risk.
Outcomes
A prioritization matrix to decide which projects to pursue and which to set aside.
6.2Costing AI
Objectives
Estimate total cost, expected return and the cost of errors. Compare the options: build, buy or abstain.
Outcomes
A business case to support your investment decision and criteria to move from pilot to deployment.
6.3Managing AI and managing with AI
Objectives
Govern your teams’ uses and use AI as decision support, with defined oversight and responsibilities.
Outcomes
The foundations of a usage policy and a dashboard specifying what leadership must receive and require.
Tools that stay in your organization
- Prioritization matrix and build, buy or abstain grid
- Profitability analysis model and business case
- Deployment criteria, usage policy and dashboard
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Path 7 · 3 programs
AI in augmented selling and communications
Strengthen your commercial performance while protecting what gives your client relationships their value.
Produce more, personalize exchanges, speed up prospecting: the gains must serve your strategy and preserve trust. Learn to govern your content, your client data and your automations, up to the risks of deepfakes and brand impersonation.
- Who is it for?
- Marketing and communications leaders, sales teams, client relationship managers, SME owners and self-employed workers.
- Prerequisites
- No prior technical or legal knowledge required.
7.1Intellectual property
Objectives
Examine content provenance, licences, usage rights and the protection of people’s voice and image.
Outcomes
A rights checklist and a protocol to assess generated content before it is published.
7.2Integrating responsible AI in sales and communications
Objectives
Build AI into your sales cycle by defining what you entrust to it, what you check and what stays in the representative’s hands.
Outcomes
Verification and governance practices to personalize your exchanges, protect client data and oversee your sales agents.
7.3The deepfake influencer
Objectives
Govern virtual influencers and synthetic content, spot targeting biases and prepare your response to a deepfake.
Outcomes
A labelling protocol and a response plan to protect the integrity of your communications and your brand’s reputation.
Tools that stay in your organization
- Rights checklist and labelling protocol
- Client data map and conversational agent profiling template
- Response plan for a deepfake or brand impersonation
Depending on the programs taken. The tools are worked on your cases and adapted to your context.
Our approach
Your reality becomes the material of the training.
Each block starts from a real case and ends with a tool worked on that case. Principles, standards and requirements take on meaning in the decisions you have to make.
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01
Your situation
Start from what you are living.
Before the training, you share one or two AI use cases. Examples, vocabulary and exercises are adapted to your sector, your role and the tools you use.
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02
Putting it into practice
Exercise your judgment.
Analyze a tool, evaluate a vendor, cost a project or respond to an incident. The training alternates demonstrations, case studies, discussions and simulations.
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03
The tools
Leave with what you need to act.
Grids, matrices, templates, protocols or roadmaps: you move your case forward and have tools to adapt, have validated and reuse in your organization.
A targeted program or a complete path.
Choose the depth that fits your need: a talk to open the conversation, a masterclass to go deeper into an issue, a training or a workshop to work on your practices.
8 hours
Time to work on your cases
Per training program, over two half-days of 4 hours. The length of talks is adapted to the event.
2 to 12
A format suited to your team
Participants per training or workshop. On site in your organization, online or hybrid. Talks welcome larger groups.
1 or 2
Simple preparation
Real cases to send before the training. Each participant brings a laptop. Prerequisites are specified for each path.
Linking principles to business decisions.
identifiable’s approach translates reference frameworks into useful practices: knowing where AI deserves its place, which responsibilities to define, which controls to put in place and which results to evaluate.
The content adapts to your role: a strategic perspective for leadership and the board, an operational approach for teams.
Read Wissam Daibess’s profileRecognized frameworks, applied to your context.
- OECD Principles
- NIST AI RMF
- ISO/IEC 42001 and 42005
- Law 25
- EU AI Act
- CASL
- Montréal Declaration
- Trustworthy AI Cycle
- identifiable’s iDIA framework and AI Index
References are drawn on according to the programs, your sector and the requirements that apply to your organization.
Which training fits your challenge?
Six questions come up again and again with leadership teams. Start from yours: the tool recommends the services and paths that address it.
Which training to choose?Which training builds a trustworthy AI practice?
Trust is built on named principles, clear roles and understood obligations. Start with Ensuring a Responsible AI Practice, then Compliant AI.
Which training prepares teams for AI?
Ready teams know what AI does and does not do, and where it is changing their work. Start with Securing your future in the age of AI, then the path for your function.
Which training keeps AI under control?
Keeping AI under control means governing, mapping, measuring and managing it, one NIST AI RMF function at a time.
Which training covers data and AI sovereignty?
Sovereignty translates into vendor criteria, contract clauses and deployment choices, at the real price of control.
Which training covers AI exposure and security?
Exposure is found by mapping what has already entered the organization, and verified through red teaming and attack testing.
Which training manages AI risk?
Every efficiency gain carries a cost of error. Put a figure on it, set your risk tolerance, then treat and document the residual risks.
Before choosing your training
Do you need to take the whole path?
Each program can be taken on its own. You can target a specific need or combine several programs into a path. The levels and prerequisites shown help you choose the right starting point.
Is the training adapted to our sector?
Yes. Examples, vocabulary and exercises are adapted to your sector and your tools. Situations can involve professional services, retail, manufacturing, aerospace, financial services, health, non-profits or the public sector.
What can we use after the training?
Depending on the programs taken, you keep the grids, templates, matrices and protocols worked on during the training. They are starting points to adapt and have validated by the people responsible in your organization.
Is the training a formal compliance assessment?
The training passes on knowledge, methods and practice tools. It does not replace legal advice, a cybersecurity audit or a formal compliance assessment. ISO/IEC standards serve as teaching frameworks; the audit of a standard rests with an accredited body.
Your next step
Which decision do you need to master better with AI?
Start with a free diagnostic to situate your practices and set your priorities. Then choose the training that answers your organization’s challenges.
Published: September 2026 · Updated: September 24, 2026
Your teams make the difference between using AI and getting value from it.
Give them the skills to choose the right uses, assess the gains and master the risks. Training built on your real cases, to make better decisions and keep control over what you entrust to AI.
You move your challenges forward during the training. You leave with tools to act.