Preparing for the AI Act: A Practical Checklist

BI,White Paper

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST

The European Union’s AI Act introduced a comprehensive regulatory framework aimed at managing the risks and ethical implications of AI systems. To remain compliant, organizations must assess their AI applications, implement effective data governance, and create robust frameworks for data management and logging.

This checklist provides a structured approach to help you evaluate and prepare your AI systems.

By following this checklist, you can gain a clear understanding of the steps required to align your AI systems with the AI Act.

Regular assessment, prioritization of risk-based actions, and the establishment of robust data governance and monitoring processes will help create a strong foundation for managing AI risks.

Continuous monitoring and adjustments to your approach will be essential as the regulatory environment evolves.

Preparing for the AI Act requires a proactive and comprehensive approach.

By taking the necessary steps to assess, manage, and monitor your AI systems, you can ensure compliance, mitigate risks, and foster trust in your AI applications.

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST © SCALEFREE INTERNATIONAL GMBH 2024

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ASSESS YOUR AI SYSTEMS

— Identify AI applications:

Create an inventory of all AI systems currently in use, including those under development.

— Categorize by risk:

Evaluate each AI system to determine whether it falls under high- risk, limited-risk, or minimal-risk categories. High-risk systems typically impact sectors like healthcare, finance, and employment, or involve biometric identification.

— Categorize by subject:

Find out whether you are a provider, deployer, importer, or distributor of an AI system.

— Document findings:

Record the risk level and reasons for classification for future audits.

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST © SCALEFREE INTERNATIONAL GMBH 2024

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DEVELOP AN ACTION PLAN WITH A FOCUS ON THE AI ACT

— Review assessment outcomes:

Analyze the findings from your assessment in relation to the requirements of the AI Act. Identify critical areas that require immediate attention, especially high-risk applications that may pose compliance challenges.

— Prioritize interventions:

Create a prioritized list of necessary actions based on risk level, legal urgency, and alignment with business objectives to ensure timely compliance with the AI Act.

— Allocate resources and timelines:

Define clear responsibilities, budgetary resources, and timelines for implementing each action, ensuring that regulatory requirements are met effectively.

— Monitor and adapt:

Continuously track progress and adjust the action plan as needed, particularly in response to evolving AI Act requirements or emerging risks.

The action plan you are creating should consider the following (not conclusive):

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST © SCALEFREE INTERNATIONAL GMBH 2024

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ESTABLISH A ROBUST DATA GOVERNANCE FRAMEWORK

— Define policies and procedures:

Create clear guidelines for data management, including data quality standards, access controls, and roles and responsibilities.

— Implement training programs:

Educate staff on data governance principles and compliance requirements under the AI Act.

— Review and update policies:

Regularly assess governance policies to align with evolving regulations and business needs.

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST © SCALEFREE INTERNATIONAL GMBH 2024

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IMPLEMENT A DATA PLATFORM POWERED BY DATA VAULT 2.0

— Design and deploy architecture:

Build a Data Vault 2.0 architecture to ensure scalability, agility, and historical tracking of data changes.

— Integrate existing data sources:

Consolidate data effectively in the Data Platform while maintaining data lineage.

— Support various data types:

Leverage the Data Platform to manage structured, semi-structured, and unstructured data, which are vital for AI applications.

PREPARING FOR THE AI ACT: A PRACTICAL CHECKLIST © SCALEFREE INTERNATIONAL GMBH 2024

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DEVELOP AN AI-MART FOR TRAINING DATA MANAGEMENT

— Create a specialized AI-Mart:

Establish a dedicated AI-Mart within the Data Platform for storing and curating datasets used for training, validating, and testing AI models.

— Establish data curation processes:

Ensure datasets are clean, relevant, and compliant with AI Act requirements.

— Maintain comprehensive metadata:

Keep detailed metadata for each dataset, including data sources, transformations, and usage history.

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INTEGRATE AI MODEL LOGGING AND MONITORING

— Set up automated logging:

Capture key details of AI model activities, including input data, feature transformations, and output decisions.

— Feed logs into the Data Platform:

Continuously integrate model logs into the Data Platform to create a centralized repository for tracking AI operations.

— Ensure structured logs:

Design logs to facilitate easy querying and reporting, aiding compliance and auditing efforts.

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ENJOY YOUR COMPLIANT DATA PLATFORM!

With your compliant Data Platform in place, you are ready to manage AI data responsibly and confidently.

Your new setup not only aligns with regulatory requirements but also provides an adaptable, secure, and transparent foundation for all your AI applications.

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