Employees, managers, leadership, operations, and IT, data, and security teams.
Practical AI training and AI literacy
Practical AI training for the work your team already does.
Employees, managers, and operations teams learn to use AI safely in their own work. We base the training on one real process so participants leave with clear rules, realistic tests, and a practical next step—or a clear reason not to automate it.
One real process, from safe model use to a decision about what is worth automating.
Shared rules, role-specific examples, and a concrete outline of the next step.
Role-based content
One shared foundation, practical exercises for each role.
The team develops a shared vocabulary, security rules, and a method for checking results. We adapt the practical work to the decisions each role actually makes.
Employees and specialist teams
Define a task, supply useful context, work with documents, check sources, and recognise situations where AI should not be used.
Managers and process owners
Identify bottlenecks, record the current results, assign accountability, and decide which steps require human confirmation.
Operations, IT, and data
Internal-system access, data quality, least-privilege permissions, action logs, evaluations, exceptions, and safe fallback to manual work.
Leadership, security, and compliance
AI capabilities and limits, accountable ownership, acceptable risk, provider selection, and questions to ask before a pilot or purchase.
One real process
The training ends with a plan you can use—not just a presentation.
Participants bring a process from their own work. We break it down precisely enough to see where AI helps, where it does not, and what must be tested before deployment.
- Map the input, steps, systems, decisions, output, and owner of the process.
- Separate AI assistance, conventional automation, and work suited to an AI agent.
- Define permitted data, required access, and actions that need human approval.
- Create realistic test cases, including incomplete, incorrect, and sensitive inputs.
- Select a success measure: cycle time, manual effort, quality, errors, or response time.
Practical format
From a shared foundation to the next safe step.
Understand
Models, assistants, agents, and automation explained through business decisions, without unnecessary technical jargon.
Practise
Business exercises covering useful context, structured outputs, fact checking, and working with sources.
Set boundaries
Rules for data, accounts, permissions, human confirmation, escalation, and handling an incorrect result.
Apply
Leave with a process outline, priorities, risks, test cases, and a named owner for a small pilot or internal change.
Security and data
Rules need to be clear before a tool becomes part of daily work.
The training connects productivity with responsibility. Teams learn to verify outputs, protect data, and recognise when a decision must remain with a person.
- Which tools and business accounts are approved for each kind of task.
- Which personal, confidential, or proprietary data must not be entered without appropriate controls.
- How to check facts, sources, calculations, and completeness before using an output.
- When human confirmation, a second review, or escalation is mandatory.
- Who owns the process, rules, access, incident response, and periodic quality review.
AI literacy
Training tailored to the people, context, and level of risk.
Article 4 of the EU AI Act requires providers and deployers to support the development of AI literacy among staff and other people dealing with the operation and use of AI systems on their behalf. Measures should reflect technical knowledge, experience, education and training, context of use, and the persons or groups on whom a system is used. The current consolidated text does not require a guaranteed specific level for every individual. That is why we adapt the programme to each role and to how AI will actually be used.
Training supports AI literacy and responsible practice, but does not by itself guarantee legal compliance and is not legal advice. Obligations depend on the organisation’s role, the specific system, and how it is used. Additional official context is available in the European Commission’s AI literacy questions and answers.
Related topics
Continue from training to practical deployment.
Questions
Before planning the programme.
Is the training for beginners or experienced users?
We establish the starting level before the session. The common foundation covers safe and verifiable use, while exercises and depth are adapted to participant roles, tools, and experience.
Is the programme tied to one model or provider?
No. We can use tools already approved by the company, but focus on transferable principles: context, task structure, verification, permissions, evaluations, and ownership.
Can the workshop produce an automation proposal?
Yes. When there is a suitable process and enough context, the outcome can include a process map, risk and approval list, initial test cases, and a short proposal for a focused pilot with clear limits.
Does completing the training make a company compliant with the AI Act?
No. Training can form part of AI literacy measures, but does not prove or guarantee overall legal compliance. A legal assessment needs to consider the specific role, system, data, and use.
First step
Tell us who the training is for and which process you want to improve.
Include participant roles, current tools, and one real business challenge. We’ll reply with a practical training format.