AI and machine learning (AI/ML) are revolutionizing technology but face increasing scrutiny from global regulators demanding rigorous transparency and accountability. The rapid development pace and significant power of AI/ML technologies have widened the scope of risk assessment, with regulators concerned about data privacy, intellectual property, and potential negative impacts like algorithmic bias or misinformation. Europe's comprehensive regulations, such as the European Union Artificial Intelligence Act, impose strict compliance requirements, with potential penalties for non-compliance, while the US and other countries are developing their own legislative frameworks. To address these challenges, an integrated approach like Continuous Compliance Automation (CCA), exemplified by JFrog's Evidence Collection, can help ensure compliance by automating security and regulatory processes throughout the AI/ML model lifecycle. This approach supports developers, security teams, and stakeholders in maintaining a trusted environment, offering a reliable path to production that aligns with compliance obligations.