1. Purpose
Bitdefender is committed to the responsible development, deployment, and use of Artificial Intelligence (AI) technologies.
This Responsible AI Policy defines the principles and governance framework that guide the lifecycle of AI systems across Bitdefender. The policy reflects industry best practices and applicable legal and regulatory requirements.
Responsible AI is integral to our mission of delivering trusted cybersecurity technologies.
2. Definitions & Scope
AI Model: A computational model developed internally or obtained from a third party that has been trained on data to perform specific tasks such as prediction, classification, generation, or decision support.
AI Agent: A software-based system or application that leverages one or more AI models (internal or external) to autonomously or semi-autonomously perform tasks, interact with users, make recommendations, or trigger actions within defined operational parameters.
AI Data Governance: AI data governance requirements shall be applied proportionally based on the organization’s level of control over the AI model and related data processing activities. This includes considerations such as whether the model is internally developed, externally hosted, or accessed via third-party APIs, as well as the organization’s ability to influence training data, processing logic, and output handling.
This policy applies company-wide and covers:
● AI and machine learning systems embedded in Bitdefender products and services.
● Classical machine learning models (e.g., statistical models, decision trees, SVMs).
● Neural networks and deep learning systems.
● AI systems used for detection, classification, filtering, ranking, prediction, correlation, or automated decision-support.
● AI systems used in research, development, quality assurance, and operational processes where AI outputs influence product behavior or internal processes.
This policy is technology-neutral and applies regardless of the specific AI architecture used. This Policy applies to both: AI Models, including internally developed and externally sourced machine learning or generative models and AI Agents, defined as software applications or systems that embed, orchestrate, or interact with AI Models to perform operational tasks.
3. Responsible AI Principles
Bitdefender structures its Responsible AI governance around the following core principles:
3.1 Transparency
We provide appropriate transparency regarding our AI-enabled capabilities:
● We clearly define the purpose and intended use of AI systems, where necessary, including limitations and unsupported uses.
● We communicate, at a high level, how AI contributes to product functionality.
● We avoid misleading representations of AI capabilities.
● Where relevant, we clarify whether AI outputs are subject to human oversight.
In the cybersecurity context, AI systems primarily support automated detection and technical decision-making rather than direct human profiling.
3.2 Accountability & Governance
Bitdefender maintains clear accountability structures for AI systems:
● Defined ownership for AI models and systems.
● Defined responsibility for data governance and model performance.
● Cross-functional review involving engineering, security, legal, and privacy stakeholders where appropriate.
● AI-related risks are managed within established security and incident response frameworks.
Responsible AI compliance is embedded into product lifecycle management processes.
3.3 Reliability, Safety & Security
AI systems are developed to meet Bitdefender’s standards of reliability and operational safety:
● Models are tested and validated before release in order to be complient with existing performance, safety, and privacy standard.
● Performance standards are defined and monitored.
● Edge cases and potential failure modes are assessed.
● Monitoring mechanisms detect degradation or unexpected behavior.
● Retraining and updates follow controlled procedures.
● Data processed is limited to what is necessary for cybersecurity purposes and handled in accordance with applicable data protection and security requirements.
Given Bitdefender’s cybersecurity focus, additional attention is given to adversarial robustness and resilience against manipulation.
3.4 Privacy & Data Governance
AI systems are developed and operated in compliance with applicable data protection laws and Bitdefender's Privacy and Data Protection Policies regarding :
● Lawful and purpose-limited data processing.
● Application of data minimization principles where feasible.
● Use of appropriate technical and organizational safeguards.
● Controlled and role – based access to training and operational datasets.
● Implementation of anonymization or pseudonymization measures where appropriate.
3.5 Fairness & Risk Mitigation
While Bitdefender AI systems are primarily designed for cybersecurity threat detection and not for automated decision-making about individuals:
● We assess models for unintended bias where applicable.
● We evaluate potential risks arising from AI outputs.
● Human oversight mechanisms are implemented where necessary to mitigate risks.
● We continuously review system behavior to identify and address unintended impacts.
● We design and deploy AI-enabled systems with consideration for recognized accessibility standards (e.g., WCAG), aiming to ensure that user interfaces, documentation, and interactions are inclusive and usable by individuals with diverse abilities.
● We are committed to continuously improving accessibility and addressing identified gaps to enhance usability and promote equal access, as reflected in our public Accessibility Statement.
3.6 Inclusiveness
We design AI enabled cybersecurity solutions to be accessible and effective across diverse users, environments, and use cases, supporting a broad range of organizational and individual security needs.
4. AI Lifecycle Management
AI Data Governance, including data source validation, quality controls, bias assessment, legal compliance, security safeguards, and traceability, is applied across each stage of the AI lifecycle
Responsible AI principles are integrated throughout the AI lifecycle:
Design
● Clear definition of intended purpose.
● Risk and impact evaluation.
Development
● Secure development practices.
● Dataset governance.
● Model validation and performance testing.
Deployment
● Controlled release processes.
● Security review prior to production.
Post-Deployment
● Ongoing monitoring and measurement.
● Model updates and retraining as necessary.
● Incident response procedures when required.
5. Regulatory & Standards Alignment
Bitdefender monitors and aligns its AI governance practices with applicable legal and regulatory frameworks, including alignment with key regulatory frameworks such as the EU AI Act, GDPR, NIS2 Directive, Cyber Resilience Act, Digital Services Act, and related EU data governance regulations.
We also consider internationally recognized AI governance principles and evolving industry best practices.
6. Continuous Improvement
Responsible AI is an ongoing commitment.
Bitdefender regularly reviews and enhances its AI governance processes to reflect:
● Technological advancements
● Regulatory developments
● Operational experience
● Stakeholder feedback
7. Public Availability
This Responsible AI Policy is publicly available to promote transparency and trust among customers, partners, regulators, and other stakeholders.