Readiness for AI ACT

Under the JSystems brand, we have been operating since 2008, initially offering training in databases, programming, and operating systems. We bring together specialists with extensive professional experience, enthusiasts of their technologies.

We are aware of the dynamic changes occurring in the IT industry, which is why we ensure that our company stays up to date. We continuously improve our program so that the IT courses we conduct reflect the current market situation. Our training is workshop-based. Each topic discussed by the trainer is supported by live coding examples. As the trainer writes code, they explain what they are doing and why. After each topic discussed in this way, the trainer leads an exercise aimed at having participants apply the technique.

A practical training on the AI Act, translating regulatory requirements into an operational compliance model that can be implemented in an organization. Participants work on classifying AI systems, roles in the supply chain, a map of responsibilities, the AI Compliance Operating Model, and the structure of the Evidence Pack for high-risk systems.

• Compliance, Legal, and Risk professionals responsible for interpreting regulations and overseeing compliance.
• AI Product Owners.
• ML, Data, and Security leaders responsible for implementing technical and control requirements.
• Transformation and Governance Leads building the AI operational model in the organization.

The goal of the workshop is to transition from understanding the AI Act regulations to defining specific actions and responsibilities within the organization. Participants will learn to classify AI systems, identify roles in the supply chain, map responsibilities, design a minimal compliance model, create the Evidence Pack structure, and establish implementation priorities.

• Reduction of regulatory uncertainty and better understanding of organizational obligations.
• Clear definition of roles and responsibilities in the AI supply chain.
• Preparation of documentation structure and evidence trail for control and audit purposes.
• Linking compliance with ISO/IEC 42001 and existing Risk, Compliance, and Security structures.
• AI systems classification map and roles matrix.
• Structure of the AI Compliance Operating Model.
• Checklist of requirements for high-risk systems.
• Structured Evidence Pack template.

Block 1. AI Act Architecture and Risk-Based Approach

• Purpose and logic of the regulations.
• Prohibited, high, limited, and minimal risk systems.
• GPAI and key concepts.
• Exercise on identifying AI systems.

Block 2. Classification of AI Systems

• Use case analysis methodology.
• Documenting decisions.
• Common mistakes.
• HR, finance, customer service, and analytics scenarios.
• Classification exercise.

Block 3. Roles and Responsibilities in the Supply Chain

• Provider, Deployer, Importer, Distributor, Integrator, Operator.
• Contractual, operational, and managerial responsibilities.
• Map of roles and responsibilities.

Block 4. Requirements for High-Risk Systems

• Risk management.
• Data quality and governance.
• Bias and validation.
• Human Oversight.
• Technical documentation.
• Event logs and information obligations.

Block 5. Evidence Pack and Implementation Plan

• Evidence-based compliance.
• Evidence structure.
• Classification and risk documentation.
• Human oversight.
• Logs and monitoring.
• Reviews and gap analysis.

2 days

• Participation in a 2-day workshop training led by a practitioner trainer.
• Training materials.
• Practical and workshop exercises.
• Ready-made templates and tools developed during the training.
• Trainer support during exercises.