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In the past 10 years, the amount of data created, captured, and replicated globally has increased tenfold (IDC). The global datasphere is expected to grow exponentially with the increasing digitization of all aspects of our lives. Moreover, the need for access to private data will significantly rise with the proliferation of AI.

Today, digital identities and user data are primarily managed by siloed, centralized systems on the cloud. Centralized systems have an increased risk of hacks, breaches, and leaks, and are prime targets for cyberattacks because compromising one system can expose vast amounts of data. For example, the cyberattack at UnitedHealth Group’s tech unit in 2024 affected the personal information of 190 million people (Reuters 2025). Data is also often used to track people’s activities online, and unnecessarily copied and shared with third parties. The Facebook and Cambridge Analytica scandal of 2018 is one prime example.

Driven by high-profile data breaches, consumers are now demanding greater privacy, transparency, and control over their personal data. Enterprise spending on compliance has also skyrocketed as data privacy laws, such as the EU’s General Data Protection Regulation (GDPR) and Japan’s Act on the Protection of Personal Information (APPI), become stricter.

The rise of AI models and agents further complicates data privacy and emphasizes the need for robust data access protocols. These advanced AI systems rely on vast amounts of data to train algorithms and deliver personalized experiences, often drawing upon sensitive personal information, such as identity details for KYC or payment methods for transactions. In October 2024, an AI-powered call center in the Middle East was breached, and over 10.2 million interactions between consumers, operators, and AI agents were stolen by attackers (Resecurity 2024). OpenAI’s Operator agent was manipulated into bypassing ethical guardrails and carrying out phishing attacks via prompt engineering (Zurier 2025).

Secure identity and user data management remains a significant challenge today, especially with the increasing complexity of AI interactions. To protect consumers and enterprises alike, we must implement a new approach that ensures data privacy and secure access.