AI for the chief risk officer (CRO) | RSM US
Artificial intelligence and AI technologies play a crucial role in the success of the risk function within businesses. Chief Risk Officers (CROs) can utilize AI to address compliance issues, navigate data governance, and manage enterprise-level risks effectively. While developing a robust AI plan is essential, CROs may require additional support in selecting the right tools and frameworks.
The Role of AI in Middle Market Businesses
AI technologies offer a wide range of benefits and potential use cases for middle market businesses, especially in the realm of risk management. As AI continues to advance, CROs are pivotal in implementing effective AI strategies to proactively handle AI risk, establish strong governance foundations, and drive responsible AI adoption.
According to the 2025 RSM Middle Market AI Survey: U.S. and Canada, 91% of middle market executives are utilizing AI in their business practices. However, despite its adoption, many organizations express the need for external assistance in maximizing the benefits of AI tools such as generative AI.
Critical Considerations for CROs
When devising an AI strategy, CROs must focus on various key areas to mitigate risks effectively:
- Alignment: Ensure that AI governance aligns with the firm’s goals, values, and regulatory requirements.
- Consistency: Maintain uniform data practices and governance standards across the enterprise.
- Definition: Define roles and responsibilities for model evaluation criteria and oversight structures.
- Informed decision making: Clearly outline incident response protocols, stakeholder feedback mechanisms, and regulatory compliance procedures.
Risk leaders need to be aware of the usage of AI tools within their organizations to mitigate potential risks associated with data loss and security breaches. Establishing transparency, accountability, and data privacy measures with third-party AI vendors is crucial for successful AI deployment.
Ensuring Ethical and Regulatory Compliance
AI model evaluation, data governance, and end-user training are essential components in deploying AI tools effectively and ethically. Companies must validate AI models, address data privacy concerns, and comply with regulatory standards to avoid bias and security risks.
Master data management (MDM) plays a significant role in optimizing AI performance and ensuring effective data governance. Collaborative efforts across different teams within the organization are necessary to align with privacy regulations and manage data-related risks efficiently.
Challenges and Opportunities
Despite the potential benefits of AI, CROs must address challenges related to data quality, bias, and security vulnerabilities to leverage AI effectively in risk management processes. Validating AI models, adhering to regulatory requirements, and monitoring data cleanliness are critical for successful AI deployment.
AI governance has become a crucial aspect for risk leaders as they navigate the complexities of AI technologies and strive to transform their businesses. External support and guidance can enhance AI adoption strategies and reduce risks associated with AI deployment.
With the right expertise and guidance, businesses can harness the power of AI to drive innovation, manage compliance effectively, and enhance operational efficiency. Contact RSM’s experienced AI advisory team to explore how AI can revolutionize your business operations.
