Financial institutions are rapidly adopting artificial intelligence (AI) to automate regulatory monitoring, enhance anti-money laundering (AML) compliance, and enable continuous auditing and risk management. Companies such as expert.ai and Protiviti have partnered to deliver AI-powered regulatory change management solutions, while Persado has introduced agentic AI tools for marketing compliance that reportedly cut content review times by over 80%. ComplyAdvantage provides AI-based AML screening and monitoring tools for real-time risk detection. US regulators are increasing their scrutiny of AI in compliance, though regulation remains fragmented, shaped by a combination of federal guidance, executive orders, and state laws. States such as Utah, Colorado, and California have enacted or proposed legislation focused on AI disclosure, algorithmic discrimination, and data transparency. Federal initiatives emphasize explainability and transparency in AI applications. AI-driven tools are enabling real-time anomaly detection, automating manual processes, and improving regulatory reporting. Financial leaders from MindBridge, Wells Fargo, Bank of China, Gulfport Energy, and Citi note the shift from periodic to continuous auditing and the need to combine AI expertise with audit skills. Cross-functional communication is highlighted as essential for meeting regulatory expectations. AI is also being used by cybercriminals to conduct sophisticated scams, including voice cloning schemes that target victims by mimicking the voices of relatives or trusted contacts. In 2023, over $126 million was stolen from seniors on Long Island, with $74 million in Nassau and $54 million in Suffolk. Experts warn that only three seconds of audio are needed to clone a voice, and AIPRM reports that 70% of adults cannot reliably distinguish between real and cloned voices. Authorities and experts recommend safeguards such as establishing safe words for verification, being cautious with unknown callers, and promptly reporting suspicious activity. For compliance teams, best practices include adopting explainable AI models, integrating AI into workflows, and conducting regular audits to ensure regulatory alignment and minimize risks.