Data Protection Impact Assessment (DPIA)

Introduction

A Data Protection Impact Assessment, also called a DPIA is a process required under Article 35 of the GDPR to help organizations identify and minimize the data protection risks of high-risk processing activities. It is especially important when using new technologies or handling sensitive data at scale. A DPIA ensures that privacy risks are assessed before processing begins and that appropriate safeguards are in place to protect individuals’ rights and freedoms.

A DPIA is necessary when data processing is likely to result in a high risk to individuals’ rights and freedoms—such as when using automated decision-making, profiling, large-scale processing of sensitive data, or systematic monitoring of public spaces. It is required before such processing begins to ensure risks are identified and mitigated in advance. The purpose of a DPIA is not only to protect individuals but also to help organizations demonstrate GDPR compliance, avoid legal or reputational harm, and implement privacy-by-design principles from the outset.

A DPIA is required when:

• System is used for systematic monitoring in a work environment, especially if used at scale
• AI is involved
• There is a potential risk to individuals' rights

As a rule of thumb, we advise deployers to conduct a DPIA. Please refer to the additional documentation, which includes a sample and a template specifically designed for Safety AI deployments.

Titles	Explanations	Sample Document
1. Project Description Set the context for the deployment.
Project Name	Choose a clear, descriptive name	Safety AI Deployment for Logistics Area Monitoring
Description	Briefly describe what the Safety AI system will do and where. Include zone coverage, system purpose, and any special setup.	Installation of Event Gates Safety AI system on factory floor to detect and log safety-critical events involving personnel and machinery (e.g., person–forklift proximity).
Data Controller	Enter your company name—the deployer is the data controller.	XYZ Manufacturing Ltd.
Contact Person	The responsible manager or DPO handling GDPR matters.	Jane Doe, Compliance Manager ([email protected])
Date of Assessment	When you start or update this DPIA.	24 June 2025
2. Purpose of Processing Justify why personal data is processed.
	Explain the safety goals (e.g., prevent accidents, improve incident response).	To enhance occupational safety by detecting, recording, and reporting unsafe interactions between workers and moving equipment (e.g., forklifts, cranes). Data is used for real-time alerts and incident analysis.
	Be specific—link AI use to real, necessary safety functions.
	This section supports your lawful basis (usually legitimate interest or legal obligation).
3. Nature of Personal Data Processed Clarify what types of personal data are involved.
Types of data	Include video recordings, logs, system metadata.	Video footage (optional), AI-detected safety events, timestamped logs
Data subjects	Who might be captured (e.g., employees, contractors, visitors).	Factory employees, contractors, and authorized visitors who enter monitored zones
Identifiers	State whether data is anonymized or could be indirectly identifying (e.g., uniform, patterns of movement).	While names are not recorded, individuals may be indirectly identifiable via video or behavioral patterns (e.g., unique clothing, routine movement)
4. Data Flow and Storage Document how data is collected, stored, and accessed.
Processing location	Note that Event Gates Safety AI operates on edge, not in the cloud.	On-edge device at each monitored zone (no cloud transfer)
Storage location	Specify where recordings and logs are stored, how long they are kept, and who has access.	Local edge device (internal SSD)
Retention	Mention features like automatic deletion, no internet access, and secured physical access.	Video footage and logs retained for max 7 days (configurable) Automatic deletion by default
Access		Restricted to safety personnel with login credentials and physical device access
5. Assessment of Necessity and Proportionality Show that data processing is justified and minimal.
Necessity	Explain why this method (AI + video) is necessary for the purpose.	Monitoring is essential to prevent human–machine accidents in high-risk operational zones
Proportionality	Describe minimization features: zone filtering, event-based logging, optional recording.	No continuous surveillance; only event-triggered logging Recording limited to incident-related events Zones and rules configured to avoid unnecessary data capture Video recording can be disabled entirely if not needed
	Show that there’s no less-intrusive way to achieve the same safety goal.
6. Risks to Data Subjects Identify potential GDPR risks.
	Use a table to rate risks (e.g., unauthorized access, over-monitoring, inability to fulfill access requests).	See table below
	Consider likelihood, impact, and what mitigations you’ve applied.
	Event Gates features like on-edge processing, no facial recognition, and access control help reduce risk.
7. Measures to Mitigate Risks List safeguards you have in place.
Technical	Built-in system features and configurations that enforce data protection through design and technology.	On-edge processing (no cloud dependency) Optional blurring of persons in recorded footage Password-protected user interface with audit logs Automatic deletion of video and logs based on retention settings No facial recognition or biometric profiling
Organizational	Internal controls and resource management practices that govern who can access data and how systems are operated.	Data access limited to trained safety staff
Process-based	Policies, documentation, and routines that ensure consistent, compliant handling of personal data and privacy responsibilities.	Clear internal policy defining processing purposes and operational restrictions
8. Consultation Demonstrate accountability and awareness.
	Document any internal consultation with your DPO or legal team.	Internal consultation with DPO and legal department
	Note whether external advice was sought (only required for high-risk cases).	No external supervisory authority contact required at this stage
	State how data subjects are informed (e.g., signage, employee briefings, privacy notices).	Staff informed via updated safety policy and signage in monitored areas
9. Conclusion Sum up the overall risk and your readiness.
	Briefly confirm whether privacy risks are acceptable with the safeguards in place.	The Safety AI deployment at XYZ Manufacturing is deemed low risk when configured and operated as described. The system supports privacy-by-design through edge processing, role-based access, and configurable data minimization features.
	Note whether any actions are still required (e.g., install signage, finalize DPA).	No further mitigation required at this stage.
	If the system is compliant and no further risk exists, you can conclude the DPIA.