Mastering the complexities of AI risk and compliance: Trends, challenges and solutions

Is your organization ready to manage AI risks and stay compliant as regulations evolve?

Artificial Intelligence (AI) is reshaping industries around the world. Companies are leveraging AI to increase efficiency, drive innovation and remain competitive. However, as AI’s influence expands, so do the complexities surrounding its governance, compliance, and associated risks.

Organizations that establish robust AI risk management and compliance frameworks not only mitigate risks—they enable faster AI deployment, reduce time to market and maximize their return on investment. Scalable AI governance is critical as companies move from experimentation to full-scale production, making AI solutions available to external stakeholders, including customers. AI risk management is no longer just about control—it’s a key driver of AI-powered success.

Read more and delve into major trends in AI risk and compliance, the challenges businesses face and practical solutions to build responsible and trusted AI systems that comply with regulations.

Matthias Bossardt

Partner, Head of Cyber & Digital Risk Consulting

KPMG Switzerland

Understanding the landscape of AI risk and compliance

AI’s rapid evolution has made it an integral part of business processes. Governments and regulatory bodies are introducing frameworks to ensure AI is deployed responsibly. These frameworks aim to promote transparency, ethical practices, and fairness in AI systems.

To comply with regulations and mitigate risks, organizations must design AI systems that minimize bias, protect data privacy, and enhance accountability. Businesses that address these challenges head-on gain a competitive edge by fostering trust and credibility.

Key trends shaping AI risk and compliance

Regulatory developments

Governments around the world are enforcing stricter AI regulations to protect consumers and businesses. One landmark example is the EU AI Act, which emphasizes transparency, safety and accountability in AI systems. Non-compliance with these regulations can lead to significant fines and reputational damage.

Organizations that proactively adapt to evolving regulations demonstrate leadership in AI risk management and gain a strategic advantage.

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EU AI Act

Artificial Intelligence

Everything you need to know about the EU AI Act, how it affects businesses, risk-based frameworks and how to comply.

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Ethical AI and bias reduction

Ensuring fairness in AI models is a top priority. Bias in AI systems can undermine consumer trust and invite regulatory scrutiny. Businesses must develop AI governance frameworks to address bias, promote inclusivity and align with ethical standards.

By ensuring diverse data sets and monitoring for bias, organizations can mitigate ethical risks and promote positive outcomes.

Transparency and explainability

Stakeholder are increasingly demanding transparency and explainability. In critical sectors such as healthcare, finance, and legal services, where AI decisions directly affect lives, understanding how AI models work is essential.

Providing clear documentation and using explainable AI models enhance compliance efforts and build user confidence.

Overcoming challenges in AI deployment

While the benefits of AI are immense, many organizations encounter hurdles when implementing AI systems. Addressing these challenges early prevents long-term issues.

Identifying and managing AI risks

A common challenge is recognizing where AI risks emerge. Data inconsistencies, algorithmic errors and lack of oversight can expose businesses to non-compliance and operational failures.

Comprehensive AI risk assessments help identify vulnerabilities. These assessments provide a roadmap for mitigating risk and ensuring long-term success.
Building strong AI governance models

Without clear governance, AI projects may lack direction and security. Robust governance ensures AI aligns with business goals and complies with regulations.

Establish AI governance frameworks that define roles, set guidelines, and embed accountability throughout the AI lifecycle.
Monitoring and validating AI systems

AI systems require ongoing monitoring to maintain performance and accuracy. Over time, models can drift, leading to unexpected biases and errors.

Implement continuous monitoring programs and regularly validate AI models. This proactive approach minimizes risk and ensures AI systems deliver consistent results.

Enterprise Risk Management (ERM) and AI

Integrating AI into Enterprise Risk Management (ERM) frameworks allows businesses to manage AI-related risks comprehensively and at scale.

Strengthening control risks

AI introduces new control risks, such as security vulnerabilities, legal challenges and operational inefficiencies. Managing these risks requires targeted mitigation strategies.

Embedding risk control mechanisms into existing ERM frameworks ensures AI-specific risks are addressed effectively.

Outsourcing AI development

Outsourcing AI development to third parties introduces additional risks. Vendors may fail to adhere to compliance standards, creating vulnerabilities.

Organizations should apply rigorous vendor evaluation protocols and establish risk transfer mechanisms to protect their operations.

Aligning IT risk management with AI

IT risk management processes must be updated to include AI-specific risks. This involves assessing the risks introduced by machine learning algorithms and ensuring robust cybersecurity measures to prevent data breaches.

Enhancing ERM Risk Management for AI

ERM risk management strategies should be expanded to address the unique challenges posed by AI systems. These strategies enable organizations to better anticipate, identify and mitigate risks related to AI technologies.

Applying KPMG’s Trusted AI framework

Deploying AI responsibly requires a structured approach. KPMG’s Trusted AI framework provides a comprehensive blueprint for minimizing risks while maximizing the potential of AI.

Key elements of KPMG's Trusted AI framework

Transparency: AI processes and decisions must be easily understood and communicated.

Ethics: Clear ethical guidelines ensure AI systems align with broader organizational values.

Governance: AI governance models enforce accountability and ensure compliance across all AI initiatives.

By applying this framework, organizations can build AI systems that are not only efficient but also trustworthy.

KPMG’s principles for responsible AI

KPMG’s approach to AI is built on three guiding principles:

Values-led

AI solutions are designed with fairness and integrity, reflecting KPMG’s commitment to ethical practices.
Human-centric

AI should enhance human potential and prioritize user needs.
Trustworthy

AI governance, privacy protections and transparent processes build trust across stakeholders.

By embedding these principles into AI strategies, organizations can mitigate risks, foster innovation and lead in responsible AI adoption.

Extending risk mitigation beyond AI

Risk management strategies should encompass broader business operations, integrating AI into the organization’s enterprise risk management framework. This approach ensures that all types of risks, including financial risks, IT risks, and natural disasters, are comprehensively addressed.

Leveraging Big Data and AI technologies

The combination of big data and AI technologies enables businesses to make informed decisions in real time. By analyzing patterns and predicting outcomes, organizations can identify risks early and implement effective risk management processes.

Continually monitoring and improving AI systems

AI systems must be continually monitored and refined to remain effective. A commitment to continual improvement ensures that AI models perform optimally and adapt to evolving regulatory requirements.

Addressing Artificial Intelligence in cyber security

AI plays a critical role in cybersecurity, helping organizations detect and respond to threats in real time. Integrating artificial intelligence in cybersecurity strategies strengthens defenses and reduces vulnerabilities to cyberattacks.

Your path to responsible AI

The journey toward responsible AI doesn’t have to be overwhelming. Organizations that proactively address AI risk and compliance challenges will mitigate risks and create an environment where AI thrives ethically and confidently.

At KPMG, we specialize in helping companies deploy trusted AI systems. By aligning with the latest regulations, adopting ethical practices and maintaining transparency, we empower them to leverage artificial intelligence in business to drive innovation and growth while ensuring compliance.

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AI Risk & Transformation

Cyber & Digital Risk consulting

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Our focused solutions

AI Risk & Compliance Assessment

We help organizations assess their current AI capabilities and prepare a strategic roadmap to unlock the full potential of AI.

Our services also ensure compliance with evolving regulations, including EU AI Act Readiness, to mitigate legal and operational risks.
AI Risk Transformation
Our transformation services are designed to build Trusted AI systems:
- AI Governance: Develop governance frameworks, operating models, and policies for ethical and secure AI adoption.
- AI Security: Design robust security strategies to protect AI systems from cyber risks, adversarial threats and privacy breaches.
- AI Development and Deployment: Establish end-to-end processes to implement and operationalize Trusted AI with resilient technologies and remediation plans.
AI Risk Monitoring
We provide ongoing oversight to ensure the reliability and accountability of AI systems:
- AI Assurance: Perform diagnostics, reviews and control testing to validate responsible use of AI.
- AI Model Validation: Evaluate model robustness, identify blind spots and mitigate bias to enhance resilience and fairness.
AI Certification ISO/IEC 42001
- Improve quality, security, traceability, transparency and reliability of AI applications
- Enhance efficiency and AI risk assessments
- Reduce costs of AI development

Are you ready to take the next step towards trusted AI?

AI technologies have immense potential to transform industries—but only if used responsibly. Compliance and risk leaders must act decisively to adapt to changing trends, tackle challenges and position their organizations for sustainable success.

Discover how KPMG’s tailored solutions can empower your organization to innovate responsibly, navigate the complexities of AI risk and compliance and drive long-term value.

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