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The recent entry into force of the European regulation on artificial intelligence, known as the AI Act, has sparked intense debate within the scientific community. Although the regulation establishes exemptions for research activities, its wording could conflict with standard practices for publishing in conferences and specialized journals. The core issue is that by sharing models, datasets, or architectures — as required by academic reproducibility standards — researchers may lose the protection of these exemptions, becoming subject to the same documentation and transparency obligations as commercial developers. This clash between regulation and scientific dynamics deserves deep reflection, especially when dealing with artificial intelligence applied to critical sectors.
For companies developing custom applications based on artificial intelligence, understanding these nuances is key not only to comply with the law but also to anticipate risks in their innovation processes. At Q2BSTUDIO, we offer AI strategies for businesses that integrate both regulatory compliance and technical excellence. For example, our teams design AI agents with full traceability, facilitating audits and the generation of documentation required by the AI Act. Additionally, we combine these solutions with AWS and Azure cloud services to ensure scalability and security, along with advanced cybersecurity that protects data throughout the model lifecycle.
Beyond regulation, the research community needs tools that allow continued publishing without compromising their legal status. Here, technology can be an ally: custom software platforms for compliance management, Power BI dashboards to visualize regulatory exposure levels, or business intelligence services to analyze the regulatory impact on development decisions. At Q2BSTUDIO, we help companies and institutions adopt these systems organically, without disrupting publication dynamics or slowing innovation. The key is to design workflows that integrate mandatory documentation as a natural part of the research process, not as an external burden.
