AI Governance & Risk

BRG’s AI Governance & Risk offering — led by nationally recognized privacy and AI governance authority Amy Worley — helps organizations embed defensibility, transparency, and accountability into every facet of their AI initiatives, ensuring that artificial intelligence is deployed responsibly, effectively, and in full compliance with evolving regulations, industry standards, and organizational values. We work with business, legal, compliance, and risk management leaders to design and operationalize the policies, oversight processes, and controls needed to manage AI-related risk in high-stakes, regulated environments.

Our approach is independent and technology-agnostic. We provide expert advisory and implementation services to help clients establish practical, auditable guardrails for responsible AI, covering everything from board-level governance frameworks to day-to-day model controls.

Core Engagements

1. AI Governance Framework & Policy Design: Design comprehensive AI governance frameworks that define how AI is overseen and enabled across the enterprise including privacy and security by design. This includes establishing governance structures (such as executive committees or steering groups), clear policies and standards for AI use, and integrating AI oversight into existing risk management and compliance processes. The result is a tailored governance model aligned with each organization’s value proposition, risk appetite, and regulatory obligations, providing a solid foundation for accountable AI deployment.
2. Model Risk Management & Validation: Implement robust model risk management practices to control and mitigate risks from AI and machine learning models. Our team develops processes for validating model performance, monitoring data quality and drift, and documenting model assumptions and limitations. We help set thresholds and testing protocols for issues like bias, fairness, and predictive accuracy, ensuring that AI models meet defined standards and that every outcome can be traced to its source data and logic. These controls give executives, auditors, and regulators confidence that AI systems are reliable and being used within acceptable risk limits.
3. Regulatory Gap Assessment & Compliance: AI risk and compliance assessments to evaluate an organization’s current AI activities and controls against emerging regulations and industry standards. From impending AI-specific laws (such as the EU AI Act) to existing data protection and model governance requirements, we map out where current practices meet obligations and where gaps exist. We then deliver actionable recommendations, and implementation plans to remediate those gaps and strengthen ongoing risk management, so that our clients are prepared for external scrutiny and regulatory reviews of their AI systems. Our goal is not just compliance but evidence-based controls that enable the business to close deals efficiently in a dynamic and fractured regulatory environment.
4. Responsible AI Controls & Monitoring: Embed responsible AI controls and continuous monitoring and observability into the AI development and deployment lifecycle. This includes integrating human-in-the-loop oversight for critical decisions, implementing audit trails and logging for AI outputs, and deploying tools to detect and mitigate bias or drift in algorithms. By integrating privacy, security, and fairness requirements into AI workflows from the start, we help ensure that AI systems remain transparent and trustworthy over time. These measures build confidence among boards, regulators, and customers that AI-driven decisions are being made with the appropriate levels of control and care.

Experience and Impact

BRG’s AI Governance & Risk offering is led by Amy Worley, Managing Director and one of the field’s most respected voices on responsible AI, privacy, and data protection. Amy’s recent book on AI governance was named an essential read by Professor Daniel J. Solove — widely regarded as the dean of privacy law, the most-cited law and technology scholar in the United States, Professor at George Washington University Law School, CEO of TeachPrivacy, and organizer of the Privacy+Security Forum — in his guide to the essential books on privacy and AI governance.

That recognition from the field’s leading academic voice reflects what our clients experience directly: a practice grounded in deep legal scholarship, hands-on regulatory experience, and pragmatic governance design that holds up under board, regulator, and litigation scrutiny.

Supporting Amy, BRG’s AI Governance & Risk team is composed of veteran risk advisors, data scientists, and industry experts – including former in-house compliance officers, a former federal prosecutor, and certified AI governance professionals – who have designed and run enterprise data governance and compliance programs in highly regulated environments and who have significant experience in regulatory enforcement. We bring deep familiarity with global AI and data regulations and regularly work with board members, executives, and legal counsel to translate new AI rules into practical, auditable action plans. Our Confidence by Design approach is based on leading research in the field with a goal of earning digital trust, which is essential in closing the gap between algorithms and human trust.

Our experience includes developing AI governance frameworks for complex multinational organizations. For example, when a global communications and technology provider needed to operationalize a new AI mandate from its CEO, BRG built an end-to-end AI governance program within the organization’s AI Center of Excellence. We helped the client align on responsible AI principles, create policies and procedures, a full-scale AI risk management framework based on NIST’s AI Risk Management Framework and ISO standards, and formal AI approval and model assessment processes – all tailored to the company’s industry and risk profile. We then worked with the client to integrate these governance processes into its existing workflow systems (including IT ticketing and compliance platforms) to ensure the new controls were adopted across the enterprise.

These efforts delivered tangible benefits. In one engagement, establishing a cross-functional AI governance council and instituting new data management practices led to a double-digit improvement in the client’s enterprise data maturity within twelve months.

What We Offer

By implementing the right checks and balances, our AI Governance & Risk services help organizations gain the rewards of AI innovation without compromising on control or trust. This approach ensures that AI is managed with the same rigor as other mission-critical processes: well-defined policies, independent oversight, and a clear record of who did what and when at each step. The result is sustainable, trusted AI solutions that leaders, regulators, and customers can have confidence in.