AI User Guidelines
To learn more about Western Digital's governance expectations:
AI Governance and Oversight Framework
Artificial Intelligence (AI) has the potential to drive efficiency, innovation, and productivity across the company. Employees are eager to explore its capabilities, but its adoption must be approached thoughtfully to mitigate risks related to data security, compliance, and ethical considerations.
To ensure AI solutions—whether built or bought—align with company priorities, security policies, and legal requirements, an AI Program Operations team has established governance policies and a structured evaluation process. Without proper oversight, we risk exposing sensitive data, misaligning with strategic goals, or investing in redundant solutions. Effective governance provides the necessary guardrails to maximize AI’s value while safeguarding the company.
Understanding AI at Western Digital
Western Digital defines Artificial Intelligence (AI) as technologies that simulate human intelligence functions. These tasks include learning, reasoning, problem-solving, understanding language, recognizing patterns, and even making decisions.
In simple terms, AI allows machines to mimic how humans think and act, but often with the speed and scale only computers can manage. There are different types of AI, ranging from basic systems that follow pre-set rules (like virtual assistants or spam filters), to more advanced models that can learn from data, adapt over time, and even generate content.
Data Privileges and Security Responsibilities
To protect sensitive information, users must maintain proper source-data privileges and ensure that only authorized data is used when interacting with AI systems. Sensitive or confidential data should never be entered into AI tools unless approved and protected by appropriate controls. Users are responsible for validating that input and output handling align with Western Digital’s security, privacy, and compliance requirements.
AI Policy Best Practices
Align AI Solutions with Business Needs
Ensure that any AI solution developed or implemented directly addresses a clear business problem or opportunity. Focus on using or creating tools that are easy for users to understand and apply, helping ensure the AI solution adds value and enhances the user experience.
Maintain a Clear Business-Level Roadmap
Develop and maintain a comprehensive list of all prioritized AI initiatives within your functional area. This roadmap should outline key milestones to ensure AI adoption is integrated smoothly and optimize existing systems and processes.
Review with the AI Program Operations Team
Periodically review your Business-Level Roadmap with key functional stakeholders to gain clear technical guidance. Before starting any AI feature development, consult with the AI Program Operations Team to align on use case taxonomy and mitigate risks.
Implement Ongoing Testing and Monitoring
Regular testing and monitoring help ensure that AI solutions remain effective, secure, and aligned with business objectives. Continuous evaluation helps identify potential issues, ensure data consistency, and maintain reliability over time.
⚠️ A human-in-the-middle review is required for all critical outputs to validate accuracy, completeness, and appropriateness before relying on AI-generated results.
