red arrow | 4crisk.ai
Back to Blogs
Posted On:
November 14, 2024

GDPR and AI Regulation: How AI-Powered Products Minimize Operational Stresses on AI Data Custody and Governance

AI helps organizations minimize operational stresses by simplifying and harmonizing their risk and compliance requirements, data custody: usage and protection and AI governance: how teams utilize, develop, or leverage AI.

In this blog, we continue the discussion from our previous article on GDPR and AI Regulation, where you can read about escalating GDPR fines, practical strategies on how organizations can adapt and how 4CRisk products can help manage compliance with these regulations.  Here we cover the recent LinkedIn compliance penalty, and focus on how organizations can minimize the operational stresses of these regulations by simplifying and harmonizing their risk and compliance requirements, specifically AI and Data Custody (data usage and protection) and  AI governance (AI systems usage; how teams utilize, develop, or leverage via a third party, any AI or data management tools).  

To level set:

General Data Protection Regulation (GDPR) - Data protection has become more important than ever for organizations with any kind of operations connected to the EU. The already well-established GDPR, which seeks to protect the personal data and privacy of individuals within the EU, as well as to standardize data protection practices across member states, is already over a half-decade old and has only grown more robust with the evolution of AI and data integration into fundamental business operations. The GDPR applies to any organization—regardless of location—that processes the personal data of EU residents, which gives it a significant global impact across an increasingly globalized supply chain.  

The EU Artificial Intelligence ACT regulatory framework adds an additional layer of complexity, overlapping with the GDPR. It aims to regulate the development, commercialization, and use of artificial intelligence (AI) systems within the European Union, with a focus on protecting fundamental rights, ensuring safety, and promoting ethical AI innovation. The AI Act is the first law of its kind globally and complements the GDPR by addressing AI-specific challenges. These two regulations overlap heavily in the areas of data usage and protection and have far reaching implications not only for organizations with any data tracing back to the EU, but also how teams utilize, develop, or leverage via a third party, any AI or data management tools.

Real-World Implications of GDPR Compliance: Lessons from LinkedIn’s €310 Million Fine

If you thought GDPR compliance was just a box-ticking exercise, LinkedIn’s recent €310 million penalty might make you think again. The Irish Data Protection Commission (DPC) issued this hefty fine after a long-running investigation into LinkedIn Ireland Unlimited Company’s data practices. What started as a complaint from the French non-profit La Quadrature Du Net in 2018 escalated into a full-blown inquiry by the DPC, highlighting just how serious regulators are about enforcing GDPR standards.

The investigation drilled into how LinkedIn handles user data, particularly regarding transparency and fairness—two foundational GDPR principles that are easy to overlook but critical to get right. LinkedIn’s practices around behavioral analysis and targeted advertising came under the microscope, with the DPC finding that the platform’s reliance on user consent and other legal justifications for data processing simply didn’t cut it. In other words, LinkedIn’s attempts at “business as usual” were deemed insufficient under GDPR’s stringent rules.

DPC Deputy Commissioner Graham Doyle summed up the issue well, noting that “processing personal data without an appropriate legal basis is a clear and serious violation of a data subject’s fundamental right to data protection.” LinkedIn’s fine is a clear signal: regulators are watching, and they’re not holding back when it comes to enforcing compliance.

For any company handling user data, the message is clear—prioritize transparency, fairness, and robust data management practices, or risk hefty penalties. With regulators tightening the reins on data processing, AI-driven tools are becoming more essential than ever to manage compliance complexities and ensure that data handling practices meet GDPR’s high standards.

Stresses on Compliance Teams Due to Increasing Complexity and Overlaps in Regulations

The introduction of regulations like the GDPR and AI Act adds significant complexity to the compliance process. These regulations require organizations to implement stringent data protection measures, conduct thorough assessments of AI systems, and maintain rigorous transparency and oversight mechanisms, all while managing existing business operations. This results in several key challenges:

  • Increased Complexity: Combining these extensive regulations creates a comprehensive framework for AI and data governance, but also a complex web of risks and compliance requirements. Organizations must navigate this carefully to ensure their operations meet standards and remain sustainable. This includes mitigating data risks and preventing regulatory risks from further complicating the process.
  • Rapid Pace of Change: Compliance, change management, and risk management teams struggle to keep up with the rapid evolution of technology, emerging risks, and the competitive landscape. Even strategic efforts in risk management and maintaining competitiveness may only be partially effective in such a dynamic environment.
  • Compliance Fatigue: The convergence of multiple regulatory frameworks can overwhelm already strained compliance and risk management systems. Organizations, especially those with limited resources, may experience compliance fatigue as they grapple with the ongoing demands of adhering to multiple, overlapping regulations. Understanding, implementing, and documenting compliance efforts across different regimes create significant stress and resource strain. Smaller businesses, in particular, may lack dedicated compliance teams, making it even more challenging to manage these complex requirements.
  • Employee Burnout: Constant adaptation to new regulations can lead to decreased efficiency, employee burnout, and compliance lapses as teams struggle to balance these demands with their core responsibilities. The pressure of meeting GDPR and AI Act requirements while striving for innovation and competitiveness in a rapidly changing market can ultimately impact the organization's agility and performance.

Key takeaway: The evolving regulatory landscape demands a proactive and adaptable approach to compliance. Organizations must invest in resources, technology, and training to navigate the complexities, mitigate risks, and ensure ongoing compliance with the latest regulations.

AI-Powered Compliance - Simplifying Through Harmonization

Organizations can avoid the increasing need to allocate more resources towards compliance efforts through the thoughtful use of AI to simplify, speed and harmonize efforts. To do so, organizations must adopt an increasingly agile and holistic view of AI and data custody efforts. They must ensure systems are not only designed to meet regulatory obligations, but to evolve with the changing landscape and to conform to emerging technologies and opportunities.  

To help develop specialized knowledge in both data protection and AI regulations, AI-powered compliance products from 4CRisk.ai can reduce costs dramatically while increasing the knowledge and expertise of compliance professionals. Advances in process mapping, data analytics, and transparent reporting empowered with AI tools can help organizations build and maintain holistic and agile systems that create opportunity amidst the uncertainty of regulatory change and rapidly evolving global conditions.  

Here are 4 core processes that, with AI, can increase accuracy and speed efforts by up to 50 times faster than current manual methods.

  1. Harmonizing through AI-Powered Regulatory Research - Your organization can build an inventory of applicable rules to your business, gathering and compiling information from multiple agencies and sources of guidance, rules, regulations, laws, and enforcement actions at lightspeed. By merging similar requirements across multiple regulatory sources significant time can be saved, up to 20x faster than current methods, and teams can use  common language in common rulebooks.  (See 4CRisk’s Regulatory Research product)
  2. Conduct Compliance Mapping Assessments to understand coverage from regulations to policies through to controls. GDPR already mandates DPIAs for high-risk data processing activities, and the AI Act reinforces this. Organizations must evaluate how their AI systems handle personal data, focusing on privacy risks and how to mitigate them by inspecting controls that support multiple regulations and international standards. By leveraging an AI-powered Compliance Mapping assessment, significant time can be saved, up to 50x faster than current methods (See 4CRisk’s Compliance Map product)
  3. Raise the bar on AI Governance with cross-functional teams: Given the increasing convergence of data protection and AI oversight, organizations need to foster collaboration between their legal, compliance, data protection, and AI development teams. This approach ensures that both GDPR and AI regulations are integrated into business processes. (See 4CRisk’s eBook on AI Strategy and Governance)
  4. Stay ahead of Regulatory updates: Compliance doesn’t end with GDPR and the EU AI Act. Organizations need to keep a pulse on evolving global data protection frameworks and ensure their practices are agile enough to adapt to new requirements, such as those in the EU-U.S. Data Privacy Framework. By leveraging an AI-powered Regulatory Change Management with Horizon Scanning, significant time can be saved, up to 30x faster than current methods (See 4CRisk’s Regulatory Change Management product) the regulatory landscape with confidence, ensuring they are well-equipped to meet current and future obligations.

The Future of Data Privacy and AI: Staying Ahead with AI

The GDPR and AI Act are setting the standard for data protection and artificial intelligence worldwide. These regulations are encouraging countries to adopt stronger privacy laws to make international business easier and better protect people's rights. Since GDPR applies to companies even outside the EU, many businesses are adopting its principles to ensure they can still serve European customers.

By using AI-powered tools for risk and compliance, organizations can not only meet these new standards but also make their compliance programs more efficient, effective, and valuable.

About 4CRisk.ai Products: Our AI products use language models specifically trained for risk, compliance and regulatory domains to automate manual, effort-intensive tasks of risk and compliance professionals, providing results in minutes rather than days; up to 50 times faster than manual methods.

Would you like a walkthrough to see what 4CRisk products can do for your organization?  Contactus@4crisk.ai  or click here to register for a demo.

4CRisk products: Regulatory Research, Compliance Map, Regulatory Change Management and Ask ARIA Co-Pilot are revolutionizing how organizations connect regulations with their business requirements.

Leave a reply

Your email address will not be published. Required fields are marked*
Thanks for commenting.
Oops! Something went wrong while adding comment..

Check out the other part of the series:

Follow our journey

Lorem Ipsum is simply dummy text of the printing and typesetting industry. Lorem Ipsum has been the industry’s standard dummy textLorem Ipsum is simply dummy text of the printing and typesetting industry.

Authors

Author

Supra Appikonda

4CRisk.ai

Co-Founder and COO

2025 Promises to be a Year of Regulatory Shifts and Emerging Challenges for Organizations

AI Game Changer: Small Language Models the Safest Alternative to LLMs for Regulatory, Risk, and Compliance Programs

GDPR and AI Regulation: How AI-Powered Products Minimize Operational Stresses on AI Data Custody and Governance