Topic

Best Practices

Best practices are established, proven methods and standards that organizations use to achieve optimal outcomes in specific domains. In AI governance and compliance, best practices encompass guidelines for responsible model development, risk assessment frameworks, data handling procedures, and ethical AI deployment that help organizations reduce liability and build stakeholder trust. Following recognized best practices enables enterprises to align with regulatory expectations, avoid common pitfalls, and demonstrate due diligence to regulators, customers, and the public.

1 item

Corporate PolicyUS2026-07-01

Databricks Enterprise AI Governance Guide Puts Risk Classification and PII Controls at the Center of Program Design

Databricks published a practitioner-oriented guide outlining best practices for enterprise AI governance, recommending that organizations inventory and classify AI use cases by risk level before applying controls. The guide emphasizes cross-functional role assignment, built-in safeguards for personally identifiable information, and proactive monitoring across the AI system lifecycle. It targets enterprise compliance teams building or maturing AI governance programs on data and model platforms.

Databricks risk classification AI lifecycle data lineage PII controls enterprise AI governance best practices cross-functional ownership