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Transforming AI into reliable advantage — governance that protects, explains and scales.
As artificial intelligence reshapes business operations, risk and compliance functions face mounting pressure to navigate escalating regulatory complexity while managing new risks and compliance considerations.
For internal audit, compliance and risk leaders, the question is no longer just about what AI can do, but how to deploy it responsibly. We help you build the governance foundation necessary to scale AI with confidence.
The role of governance in AI adoption
With AI advancements continuing to evolve, chief risk officers and governance leaders are key contributors in implementing an effective AI strategy to proactively manage AI risk, establish a strong AI governance foundation, and drive responsible, transformative AI adoption.
Our approach breaks AI governance into manageable steps built upon existing corporate, IT and data governance principles. Rather than starting from scratch, we help you extend and enhance the frameworks you already have in place.
Key areas we address
AI policy and regulatory alignment | Bias detection and model fairness |
| We help you navigate the evolving regulatory landscape—from the EU AI Act to GDPR and sector-specific rules. Business leaders must approach the use of generative AI in a responsible and ethical manner, with consideration given to the potential risks and impacts on their users and customers. | Multiple factors can contribute to AI monitoring and audit principles to determine model effectiveness, performance and risk management. We help you identify and address data bias, human bias, and ethical bias before they impact business outcomes. |
Model transparency and explainability | Third-party AI risk management |
| When you create an AI model with an expectation of a specific outcome, you must go back and analyse the testing data to ensure you have the right data in your AI model. We implement practices that ensure your AI outputs can be understood, explained and defended. | Many organisations are using multiple free or open-source AI models without considering the implications. We help you establish clear accountability with risk distribution between your organisation and your vendors, addressing data privacy, security and compliance aspects. |
Our governance framework
We help you establish:
Proactive planning to identify bias, privacy risks and regulatory concerns with specific key performance indicator-related impacts.
Drift monitoring to create seamless execution of statistical properties and to predict output and patterns.
Traceability and corrective actions to manage regulatory compliance and service-level agreements.
- Ongoing maintenance to ensure model viability against set goals, objectives and environment changes.
Transform AI ambition into trusted, high‑Impact outcomes
While risk leaders may understand how to devise a strong AI deployment strategy, additional support may be necessary to determine the best AI solutions and most beneficial framework. An external perspective can increase visibility into AI adoption and governance strategies, reducing the potential for reputational and financial risks.
Meet our AI governance experts
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There are more ways RSM can safeguard your business
There are more ways RSM can safeguard your business
Get in touch with our team to find out
Get in touch with our team to find out