A procedure, not a one-off trick
Every participant leaves with a procedure for their own task: how to assign the work, check the result and save a template they will reuse.
AI TRAINING FOR COMPANIES
AI training built on your work, not theory.
One day, your own documents, your own spreadsheets. People work on their own, check the output and at the end pick one use case worth developing.
RESULTThe day does not end with an experience.
The day does not end with an experience.
It ends with a procedure that works on Monday.
Companies do not fail on AI features. They fail on the missing link between the tool, the real task and the person responsible for the result.
A clear boundary, not guesswork
The team knows which data may go into which tool, what belongs only in a separate environment and where a human always has the last word.
One priority, not a list of ideas
At the end we separate what can be used right away from what needs integration, better data or further verification.
What really happens on that one day.
The exact mix is set by participant roles and the target outcome. It is a starting framework, not a presentation that fits every company the same way.
Shared foundations
What AI can do and where it fails, with no slides. The team aligns on terms and on how to check output.
Documents and research
Summaries, version comparisons, working with sources. Participants get used to verifying whether a conclusion follows from the materials, or the AI invented it.
Spreadsheets and recurring outputs
Analysis, calculation design, logic checks. AI helps with the numbers, a human stays responsible for them.
A task by role
Each group solves a task from its own agenda. Marketing does not get a finance task, finance does not get an HR task.
A small repeatable procedure
A one-off chat prompt becomes a procedure: a named input, a brief template, a checkpoint and an output that works a second and third time.
Choosing the next step
The team names several options and picks one priority. Management gets a basis for deciding what to develop and what should wait.
We prepare it so you risk no company data.
Short preparation with management
Before the training we map roles, tools in use, recurring tasks and constraints. We do not need live company data for that.
Safe trial materials
We build tasks on public, anonymised or synthetic data. Sensitive materials only under a separate agreement on environment and access.
Hands-on work instead of a demo
Participants work on their own. The instructor only corrects briefs, shows checking techniques and explains why an output passed or failed.
Follow-up verification
After the training we check which procedures the team actually uses and where it got stuck. Adoption is a separate step, not a hidden promise of the training day.
BY ROLEThe same tool.
The same tool.
Different work, different responsibility.
Decisions on where AI makes sense
An opportunity map, tool selection criteria, a process owner and conditions for limited verification before a decision is made.
Materials without automated decisions about people
Drafting texts, structuring materials, checking consistency. A human always decides about people in the end, not a model.
Research and a first draft with source checks
Working with materials, message variants, reformatting. References and numbers are verified, not invented.
Documents, spreadsheets and a regular report
Data extraction, calculation design, a checklist for a recurring output. A number without a source never appears in the report.
Security and the AI Act as usable guardrails.
We do not teach paragraphs as the main product. We tie rules to the work people do and the tools they actually use.
- which data the team may enter into which tool;
- which outputs must always be verified against the source, not just against an impression;
- where AI prepares a draft and where it must never decide alone;
- who approves a new tool, integration or automated procedure;
- how training and every change of the tools in use is recorded.
QUESTIONS
Questions asked before the training.
Is the training suitable for people without technical knowledge?
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Yes. The programme builds on everyday work with documents, spreadsheets and research, not on programming. Technical teams can get their own advanced scenario.
Do you use our company data in the training?
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By default, no. We work with public, anonymised or synthetic materials. We handle sensitive data only after a separate assessment of environment and access.
Does the training itself satisfy the AI Act?
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Not fully, but it is a documentable step toward it. Article 4 of the AI Act, as amended by Regulation (EU) 2026/1744, asks for measures supporting AI literacy by role and actual AI use. It is an obligation of effort, not of result, a company does not have to guarantee a specific level for any individual, and the regulation prescribes no single course or stamp. CIAD supplies the syllabus, attendance records and role-based rules.
How much does the training cost?
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No public price list sets the price. It depends on the number of roles, scenarios and the format of the day. After a short introductory consultation we send the scope and a quote.
What happens after the training?
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The company can stay with the procedures and rules it received, or follow up with a pilot of one use case. The next step has its own scope and a measurable goal.
NEXT STEPDescribe your team roles and work.
SEND A TRAINING INQUIRYDescribe your team roles and work.
We will reply with a format that fits.
The introductory consultation defines the goal, preparation and outputs. Pricing follows the concrete scope, not a price list.