Data privacy and document management in the AI era

Data privacy has evolved from a compliance checkbox into a strategic business imperative. This session moves beyond regulatory basics (like GDPR), focusing on the practical challenges of managing Personal Identifiable Information (PII) within complex, AI-driven ecosystems. How can organizations effectively implement Privacy-by-Design and Privacy-by-Default principles across distributed environments?

We will explore how advanced technologies, such as Federated Learning and Homomorphic Encryption, allow sensitive data processing without exposing the underlying risk. The discussion will highlight how the Data Protection Officer (DPO) role is transforming into a strategic partner, driving innovation while ensuring robust governance.

Key Discussion Points:

• Balancing AI innovation with effective data minimization and anonymization;
• Practical approaches to data governance across international jurisdictions;
• Leveraging privacy as a competitive advantage.

A significant amount of critical corporate knowledge remains trapped in unstructured format – contracts, invoices, and reports. This session explores how Intelligent Document Processing (IDP), powered by Large Language Models (LLMs) and Vector-based knowledge systems, are fundamentally redefining corporate documentation. It’s no longer just OCR; it’s about semantic understanding, classification, and real-time knowledge extraction.

We will discuss the journey from a passive archive to an active, intelligent knowledge center that supports automated workflows and instantaneous decision-making. The focus will be on the practical implementation challenges and the massive ROI generated by automating end-to-end document processes.

Key Discussion Points:

• Mitigating the risks of LLM hallucination and accuracy in IDP;
• Implementing Retrieval-Augmented Generation (RAG) systems for secure and precise knowledge retrieval;
• Measuring the real-world return on investment (ROI) in document automation.