AI-driven Risk assessment in GDPR compliance: Real Time NLP and Machine Learning-based Gap Analysis of Data Protecting activities

Conference papers

Authors

Izuchukwu Patrick Udechukwu , Knut Haufe , Reiner Creutzburg , E. Faith Yetkin and Adeopatoye Remilekun Jakobs

Abstract

The General Data Protection Regulation (GDPR) necessitates efficient, scalable compliance tools. Traditional audits are time-consuming and error-prone, hindering the management of dynamic data processing activities. This research proposes an AI-powered real- time GDPR compliance auditing framework, using Natural Language Processing (NLP) to analyse legal texts and data. The system detects compliance gaps and provides actionable insights for compliance officers. By integrating NLP and Machine Learning, the framework ensures transparency, helping organisations streamline compliance and mitigate risks in a constantly evolving regulatory landscape.

Keywords

GDPR Compliance, AI-driven Risk Assessment, Natural Language Processing (NLP), Compliance Automation