AI ethics, governance & compliance

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Artificial Intelligence (AI) is transforming industries by driving efficiency, automation and new business opportunities. However, organisations struggle to scale AI from proof of concept to full enterprise-wide integrations while ensuring regulatory compliance, data governance and ethical AI use.

As AI adoption accelerates, regulatory frameworks introduce new expectations for transparency, accountability and compliance. Organisations must implement strong AI governance structures to ensure ethical AI deployment while maintaining business agility.

At KPMG, we help organisations navigate AI regulations and establish governance frameworks that foster responsible AI innovation. We believe that compliance and AI governance should not be seen as constraints but as enablers of trustworthy and scalable AI solutions. We take a proactive approach to compliance, helping organizations balance AI’s business potential with legal and ethical responsibilities, ensuring value creation in a safe and compliant way.

Jens Krenk

Partner, Advisory

KPMG in Denmark

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We help organizations evaluate the current state of their AI initiatives and determine their readiness to comply with emerging regulations such as the EU AI Act and other global standards. Our team performs detailed assessments of AI systems, governance frameworks, documentation practices, and risk controls.

Based on these findings, we design tailored action plans to close compliance gaps, enhance governance maturity, and build a scalable foundation for responsible AI deployment across your organization. We work collaboratively to ensure readiness is not a one-time effort, but an ongoing capability embedded into the organization.

We help organizations establish the data foundations necessary for responsible and compliant AI systems. Our services include designing data governance frameworks that promote data quality, integrity, lineage, security, and appropriate use. We assist in setting up transparent processes that enable organizations to document and explain how data is collected, processed, and used in AI models.

By strengthening data governance and embedding transparency practices, we help ensure that AI systems are built on reliable, bias-free data and that their decision-making processes can be clearly understood and communicated to regulators, customers, and other stakeholders.

We can help develop and embed AI compliance programs that are integrated into broader corporate governance and risk management structures. This includes drafting AI-specific policies, defining roles and responsibilities, establishing model risk management processes, and building monitoring and reporting mechanisms tailored to AI use cases.

Our approach ensures that AI governance is not siloed but aligned with enterprise risk, compliance, legal, and technology functions. We help organizations build sustainable programs that evolve with regulatory expectations, enabling long-term resilience.

We support organizations in proactively identifying and addressing ethical risks associated with AI development and deployment. This includes evaluating AI models for issues such as bias, unfair treatment, lack of explainability, and unintended consequences.

Our approach combines technical assessments with ethical frameworks to create a holistic view of AI risks across the system. We then help organizations implement mitigation strategies that align the use of AI with organizational values, customer expectations, and regulatory demands.

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