Compliance or Innovation? The Balancing Act for Startups Under the AI Act

Athanasios Davalas, Anna Angelaki, Dr. Christos P. Beretas

Citation: Athanasios Davalas, Anna Angelaki, Dr. Christos P. Beretas, "Compliance or Innovation? The Balancing Act for Startups Under the AI Act", Universal Library of Engineering Technology, Volume 02, Issue 01.

Copyright: This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

This paper explores the unique challenges and opportunities that the European Union’s Artificial Intelligence Act (EU AI Act) presents for emerging startups across Europe. The Act aims to create a framework that emphasizes trust and ethical considerations in how artificial intelligence technologies are used. As a result, startups must navigate strict compliance requirements while also being key players in driving innovation. The analysis highlights some significant hurdles that the Act imposes, particularly for startups that often have limited resources. These challenges can be financial, operational, or strategic in nature. However, the study also looks at ways to balance the need for compliance with the need for flexibility and innovation. Potential strategies include using regulatory sandboxes, adopting risk-based compliance frameworks, and fostering collaborative partnerships. In conclusion, the paper suggests policy changes aimed at simplifying compliance processes, improving supportive infrastructures, and helping startups flourish in a landscape that is both regulated and focused on innovation. By tackling these intricate dynamics, the research underscores the potential for European startups to lead the way in the responsible development of AI technologies while still preserving their competitive edge in the market.


Keywords: EU AI Act, European Startups, Artificial Intelligence Regulation, Compliance Challenges, Innovation Strategies, Regulatory Sandboxes, High-Risk AI Systems, Ethical AI Development, Policy Recommendations, Responsible AI Innovation.

Download doi https://doi.org/10.70315/uloap.ulete.2025.0201001