Ensuring Compliance with the EU AI Act
The EU AI Act establishes a comprehensive regulatory framework for Artificial Intelligence (AI), requiring companies operating in Europe to meet new standards for transparency, data quality, and bias reduction, effective intermittently over the next few years.
Understanding the New Standards
Businesses must categorize their AI solutions by risk level and ensure compliance through diligent data management, design controls, risk management processes, and continuous monitoring to mitigate biases and errors.
While compliance may seem burdensome, the EU AI Act presents opportunities for enhanced AI literacy within finance teams, enabling better understanding and utilization of AI to innovate and support informed decision-making.
Compliance Requirements for AI Providers
Different AI providers, deployers, and importers will be categorized based on their risk level. Companies operating in the EU must understand their categorization and what they need to do to remain compliant with the new regulations.
Transparency and Bias
To help companies understand how to accommodate both their AI ambitions and the new law, key industry leaders have elucidated how finance applications may be affected.
While the Act doesn’t classify most finance AI applications as high-risk, it introduces intriguing new compliance requirements. Finance teams now face the challenge of ensuring transparency and documentation in AI systems, particularly those for payments and fraud detection. Developers and deployers must ensure that end-users are aware that they are interacting with AI, like chatbots and deepfakes.
The act’s transparency requirements will go into effect on August 2, 2025.
Data Quality and Governance
Data quality and governance is another major emphasis of the EU AI Act that businesses should be aware of. To remain compliant, companies should ensure that they have:
- Data Management Procedures: Implement protocols for data acquisition, collection, analysis, labeling, storage, filtering, mining, aggregation, and retention.
- Design and Development Controls: Ensure systematic actions for the design, verification, and validation of AI systems.
- Risk Management Processes: Identify, assess, and mitigate risks associated with AI system operations.
- Data Suitability: Utilize datasets that are relevant, representative, free of errors, and as complete as possible to minimize biases and inaccuracies.
- Continuous Monitoring: Regularly assess data quality throughout the AI system’s lifecycle to detect and address potential issues promptly.
Implications for Businesses
AI is an essential service and now has to be regulated like one. Almost 70% of business leaders plan to invest between $50 to $250 million in AI over the next year, up from 51% the year before. Clearly, AI technology is not going anywhere. Companies now need to be prepared for their AI practices to be scrutinized in the same way other essential workflows, like tax practices, would be.
It’s crucial for companies to ensure compliance even with low-risk AI solutions. Although the EU AI Act largely targets Generative AI and other use cases with more potential harm, companies leveraging AI for financial purposes should also be cognizant of the new regulations. Adopting solutions from compliant partners will be essential.
Furthermore, the Act emphasizes the importance of AI literacy within finance teams. As CFOs and teams understand this technology better, they will unlock potential use cases to help innovate and bolster decision-making. Companies should seize this opportunity to ensure all team members thoroughly understand AI—how to use it responsibly and how it can help achieve business goals.
