8 Key Challenges in AI Compliance

The relationship between regulatory compliance and Artificial Intelligence is a constantly evolving landscape, and the challenges we face today and in the future are increasingly complex, particularly within the legal domain. The impact is undeniable, and AI regulation remains practically scarce. In fact, while there is a European AI Act (AIA) designed to reduce and limit risks and improve user protection, it will not come into force until 2026, leaving us currently facing a regulatory gap. 

In the era of Artificial Intelligence, compliance faces new challenges, as traditional regulations must be updated to address new ethical and legal risks associated with the use of this technology, such as algorithmic discrimination, transparency in automated decision-making, and data protection. 

Simultaneously, AI can serve as a strategic ally in regulatory compliance, enabling the analysis of large volumes of data, detection of suspicious patterns, and automation of audit processes. Companies must balance technological innovation with a solid ethical framework and regulatory compliance. 

Below, you will find the 8 most important challenges that companies face in this area: 

1. AI Governance 

Clear and effective regulatory frameworks must be established for the development and use of AI, especially in sensitive areas such as automated decision-making and privacy. 

2. Algorithmic Bias 

It is essential to identify and mitigate inherent biases in AI algorithms to ensure fairness and prevent discrimination. 

3. Algorithmic Transparency 

It is recommended to develop mechanisms to make algorithms more transparent and comprehensible, allowing individuals to understand how decisions that affect them are made. 

4. Privacy in a Data-Driven World 

Protecting the privacy of personal data in an environment where data collection and analysis are increasingly common has become one of the greatest challenges for the future, according to cybersecurity experts. 

5. Generative AI 

The rapid evolution of models like ChatGPT presents new challenges regarding originality, intellectual property, and misinformation. 

In this context, there are essential areas that affect aspects such as sustainability, transparency, and business security. 

6. Originality and Intellectual Property 

How are copyright protections maintained when machines generate works that appear human-made? These questions pose complex legal and ethical challenges that must be constantly regulated to prevent plagiarism and theft of private information or images. 

7. Misinformation 

The ease with which these models can generate false or misleading texts poses a significant risk for the spread of misinformation. The ability to distinguish between human-generated and machine-generated content becomes increasingly difficult, which can have serious societal consequences. 

8. AI and Human Rights/Mass Surveillance 

It is fundamental to establish clear boundaries and ensure that surveillance is conducted transparently and respectfully toward human rights. 

These areas represent the greatest challenges for the business ecosystem in the coming years within the regulatory compliance sector, as they converge perfectly across any type of enterprise. 

Furthermore, data protection is considered one of the most important factors in compliance, recognizing that proper development of a contingency plan will help prevent any type of risk or danger that could cause tangible or intangible deterioration to the business.