Increase your capacity to create value with AI
Consulting and expertise: AI applied to your business problems. Over 20 years as an IT leader, in the service of AI you control — compliant, secure, and delivering results.
- Business
- Data
- Infrastructure
- Change management
- Legal
- Managers
- Executive committee
Fabien Baudot
AI consulting & expertise · Interim CIO
Your teams already use AI. Do you know how?
Consumer assistants, home-made automations, agents built outside any framework: AI comes into the company through the back door. It is the new shadow IT — and it exposes your data, your decisions and your compliance.
With autonomous agents comes one more question: who answers for a decision taken by a machine, and how can it be traced?
Data leakage
Client documents and internal data sent to third-party services, with no trace and no control.
Unknown reliability
Agents that decide while nobody checks their answers or can replay them.
AI Act obligations
Inventory, risk level, human oversight: the EU regulation also applies to internal uses.
The AI Act in two minutes
The regulation classifies each use of AI by its level of risk: the higher the risk, the heavier the obligations. It applies to those who provide an AI system, but also to the companies that use one in their business.
Regulation (EU) 2024/1689 of the European Parliament and of the Council of 13 June 2024 laying down harmonised rules on artificial intelligence
Published in the Official Journal of the European Union on 12 July 2024 · in force since 1 August 2024
Read the text on EUR-Lex →Regulation (EU) 2026/1744 of the European Parliament and of the Council of 8 July 2026, known as the “Digital Omnibus on AI”
Published in the Official Journal of the European Union on 24 July 2026 · in force since 27 July 2026 · postpones the high-risk deadlines
Read the text on EUR-Lex →Minimal risk
No specific obligation Outside the cases covered by the regulationSpam filters, writing assistance, recommendations: the vast majority of everyday uses.
Limited risk
Transparency Article 50Chatbots, generated content: users must know they are dealing with an AI.
High risk
Heavy obligations Article 6, Annexes I and IIIRecruitment, credit, education, critical infrastructure: risk management, documentation, logging, human oversight.
Unacceptable risk
Prohibited Article 5Social scoring, manipulation, emotion recognition in the workplace.
For every company, whatever the level: support AI literacy among the people who use it (Article 4). This already applies.
The timeline
- Entry into force of the regulation (Article 113)
- Prohibitions (Art. 5) and AI literacy (Art. 4)
- General-purpose AI models
- Transparency obligations (Art. 50)
- New prohibitions (Art. 5); labelling of content generated by systems already on the market (Art. 50)
- High risk: listed uses (HR, credit, education…)
- High risk: AI embedded in regulated products
Solid dots: in force. Hollow dots: upcoming. The 2 December 2026 and high-risk deadlines are set by Regulation (EU) 2026/1744 of 8 July 2026.
Where to start?
Knowing which uses of AI exist in your company, and which category each one falls into. That is what the AI audit is for.
AI applied to business problems
A pragmatic AI vision, from assessment to industrialisation — with the same standards throughout: quality, traceability, compliance.
AI audit & mapping
Are you AI Act compliant? I inventory the uses and agents actually in service, identify shadow AI and secure whatever poses a risk of data leakage or unreliability.
- Declared and undeclared uses, mapped
- AI Act classification of each use case
- A plan to secure shadow AI
Best practices & agent design
AI usage rules your teams understand and apply, and agents designed to be governed: an agent proposes, a human approves.
- Usage charter and best practices
- An agent design method
- Training for teams, at every level
Project management
Turning business needs into operational solutions, with particular attention to quality and traceability — from experimentation to industrialisation.
- Use cases chosen on value, data and capacity for change
- Acceptance testing and quality measurement
- Decision traceability
Digital transformation
More than twenty years serving the information systems of mid-sized companies and large accounts: the same standards, applied to your transformations.
Interim CIO
Experienced IT leadership, available immediately, for the periods when the seat cannot stay empty.
Learn more →Digital strategy
A technology roadmap aligned with the company's objectives, with milestones that can be verified.
Learn more →IT transformation
Modernise your ageing digital ecosystem and eliminate application sprawl to regain agility and performance.
Learn more →Performance & KPIs
Put in place relevant management indicators for informed decision-making and objective tracking of the value delivered.
Learn more →Training your executives and managers in AI
AI is decided in the executive committee and lived in the teams. I train those who arbitrate and those who manage, so they can decide and lead with full knowledge.
An obligation already in force: the AI Act asks companies to support AI literacy among the people who use it (Article 4).
Executive committees & leadership teams
What AI changes for your business, what it exposes — data, reliability, the AI Act — and how to choose the use cases worth industrialising.
Managers
Leading teams that already use AI: usage rules, shadow AI, keeping a human in the loop, change management.
Content built on your real use cases, illustrated with concrete examples.
Moving forward together with people who don't speak the same language
An AI or transformation project cuts across the whole company. I connect those who express the need, those who build the solution and those who decide, speaking each one's language.
Business teams
Understanding their processes and constraints, turning their needs into solutions, and solutions into tangible benefits.
Data
Data quality, availability and governance: what makes a project succeed, before any choice of tool.
Infrastructure
Hosting, security, operations: what has to hold up in production, not just in a demo.
Change management
Bringing teams on board, evolving processes and roles, tracking real adoption over time.
Legal
AI Act, GDPR, contracts: asking your lawyers the right questions and building their answers into the project.
Managers
Giving them clear rules and the means to support their teams through change.
The executive committee
Informing trade-offs: expected value, risks, costs and timeline, presented without jargon.
Clear project governance
Who decides what, when and on what information: issues reach the right level and decisions flow back down to the teams.
Discuss your project →I also put AI into production
Software I design, build and run myself: proof in practice of what I recommend to my clients.
Audit 4 portes
Is your customer base ready for e-invoicing?
Upload an extract of your customer base: the audit checks every record against public registers and tells you whether it passes the four gates — country, identification, company status, e-invoicing address.
Base Sociétés
Your customer base changes without you.
Acquisitions, mergers, closures, relocations: continuous checking of your customer master data, record by record, against public registers — duplicates, insolvency proceedings and foreign customers included.
AI Platform
Every department gets its own team of AI agents.
AI agents on your servers, with open-weight models: each department receives prepared deliverables, and its manager approves, corrects or rejects them. 100% local, zero token costs.
An IT leader with hands-on AI experience
A practitioner, not a theorist
I design and run my own agents: my recommendations are tested in real conditions.
20+ years in IT leadership
The agility of start-ups and the rigour of large groups: AI placed within your information system, your risks and your organisation.
Business value first
No AI for its own sake: use cases chosen for their value, and indicators to measure it.
What my clients say
Concrete collaborations, measurable results. Testimonials translated from French.
If everyone delivered like Fabien (in quality, professionalism, high standards, relevance and innovation), we would live in a utopian civilisation where every company would prosper and peace would reign.
Fabien BAUDOT worked with our Enedis Languedoc-Roussillon regional division, and our collaboration was very fruitful. We appreciated his diligence and the reliability of his work.
Fabien is effective to work with — passionate about technology, pragmatic, reliable. A real pleasure to have worked with him.
He coordinated the project perfectly and saw it through. Despite the pressure, he created a healthy, friendly and always highly professional atmosphere.
Fabien was our point of contact throughout the preparation of our demo for the most important trade show of the year for our entity. He was particularly effective in managing the project and his technical teams, and an invaluable help in explaining the new technologies we were going to use in plain terms. The difficulty lay in the complexity of the systems we wanted to promote; he adapted and made constructive proposals. As a result, together we developed a demonstrator able to speak both to highly business-oriented decision-makers and to more institutional visitors, who were able to understand the operational gains of a new technological solution. Thanks to Fabien, this event was a real success — our clients still remember it two years later!
Fabien supported us in setting up a virtual reality solution. What I remember is how available he always was, and his professionalism.
Fabien was quickly up and running on the project entrusted to him. His analytical skills and ability to synthesise gave us an overall view of the subject and allowed us to map out its main guiding principles. A serious and effective consultant whom I recommend.
My thinking on AI in business
LinkedIn posts are in French.
Deploying AI: a discipline in its own right, not one more project
Deploying AI is not one more project in the IT portfolio: it transforms practices, jobs and value creation. It needs its own place in the organisation chart, with a shared vision, a team, a budget and clear governance.
LinkedInMy project manager's second brain
Every morning, an AI agent analyses my information streams and feeds my project cockpit: alerts, decisions to make, action tracking. The AI proposes, I decide.
LinkedInAI: 20% technology, 80% organisation
Why do so many AI experiments fail? Because they are tackled from a technical angle. Organisational readiness is the IT department's job.
LinkedInThe AI agent: from simple tool to balance-sheet asset
AI no longer merely assists — it becomes an operational asset that encapsulates business knowledge and transforms the value chain.
LinkedInLet's control what we create: AI produces more code than ever
AI speeds up code production, but who controls quality? Why CIOs need to rethink their validation processes.
PublicationsAll my publications
Articles and posts on AI, IT leadership and e-invoicing. LinkedIn posts are in French.
Go to the Publications page →Where does your company stand with AI?
Let's talk about your uses, your risks and your priorities. A first 30-minute conversation, with no obligation.






