Automated AI Driven Data Subject Rights Request Workflow

Automated Data Subject Rights Request Handling

1. Initiation of Request

1.1 Request Submission

Data subjects submit requests via a secure online portal or mobile application.

1.2 Verification of Identity

Utilize AI-driven identity verification tools such as Onfido or Jumio to authenticate the identity of the requester.

2. Categorization of Requests

2.1 Request Classification

AI algorithms analyze the nature of the request (access, deletion, correction) using natural language processing (NLP) tools such as IBM Watson or Google Cloud Natural Language.

2.2 Priority Assessment

Implement machine learning models to assess the urgency and complexity of the request, categorizing them into high, medium, or low priority.

3. Data Retrieval

3.1 Automated Data Search

Deploy AI-powered data mapping tools like OneTrust or BigID to locate relevant personal data across various databases.

3.2 Data Compilation

Utilize automation tools to compile retrieved data into a user-friendly format for response.

4. Response Generation

4.1 Drafting Response

Leverage AI writing assistants like OpenAI’s GPT-3 to generate personalized responses based on the type of request and data retrieved.

4.2 Review and Approval

Incorporate a review step where legal or compliance teams utilize AI-driven compliance tools to ensure responses meet regulatory standards.

5. Communication of Response

5.1 Secure Delivery

Use secure communication channels (e.g., encrypted email, secure portal) to deliver responses to the data subject.

5.2 Confirmation of Receipt

Implement an automated system to confirm receipt of the response by the data subject, utilizing tools like DocuSign for electronic signatures if necessary.

6. Monitoring and Reporting

6.1 Tracking Requests

Utilize dashboards powered by AI analytics tools such as Tableau or Power BI to monitor request statuses and trends.

6.2 Compliance Reporting

Generate compliance reports automatically using data visualization tools to ensure adherence to privacy regulations.

7. Continuous Improvement

7.1 Feedback Collection

Collect feedback from data subjects regarding their experience using AI-driven survey tools like SurveyMonkey or Qualtrics.

7.2 Process Optimization

Analyze feedback and performance metrics to identify areas for improvement, applying machine learning to enhance future request handling processes.