AI has the potential to significantly assist financial firms in meeting their regulatory compliance obligations, in an emerging field known as 'RegTech' (Regulatory Technology).

Automating Compliance Tasks: Many compliance tasks involve the processing and analysis of large volumes of data. AI can automate these tasks, making the compliance process more efficient and reducing the risk of human error.

Predictive Analytics: AI can use past data to predict future regulatory risks. This can help financial firms to be more proactive in managing these risks, rather than just reacting to compliance issues after they occur.

Natural Language Processing (NLP): NLP can be used to analyze regulatory documents, extract relevant information, and map this information to the firm's internal policies and procedures.

Real-Time Reporting: AI can automate the generation and submission of regulatory reports, and can provide real-time updates to internal stakeholders about the firm's regulatory compliance status.

Examples of RegTech Solutions in Action:

1. IBM's Watson Financial Services: Watson's Regulatory Compliance solution uses AI to help firms manage their regulatory compliance. It can analyze regulatory documents, map regulations to internal controls, and help to identify gaps in compliance.
2. Ayasdi: Ayasdi offers an AI platform that uses machine learning to identify potential compliance risks. For example, it can detect patterns in transaction data that might indicate money laundering.
3. ComplyAdvantage: ComplyAdvantage uses AI to automate Anti-Money Laundering (AML) and Know Your Customer (KYC) checks. It uses machine learning to continuously update its risk database and reduce false positives.
4. Featurespace: Featurespace's ARIC platform uses machine learning to detect and prevent fraud in real time, helping firms to comply with regulations related to fraud prevention.

By leveraging AI in regulatory compliance, financial firms can not only make their compliance processes more efficient and accurate, but can also be more proactive in managing regulatory risks. However, it's important to remember that AI is not a silver bullet, and firms will need to carefully manage the implementation of AI in their compliance processes, including managing data quality and privacy, and ensuring the explainability and fairness of their AI systems.