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      At KPMG, we firmly believe in the transformative power of AI, recognising that its full potential is unleashed when coupled with human expertise and ingenuity. KPMG has always been at the forefront of leveraging new technologies to inspire confidence and empower change, blending deep industry expertise and process know-how with cutting-edge technology alliances. This helps accelerate the value derived from AI. Embracing the opportunities AI presents, shows equal dedication to deploying this technology responsibly, with a commitment to trustworthiness, safety and freedom from bias. This commitment is encapsulated in the principles, ethical pillars and governance approach known as KPMG Trusted AI.

      This is our strategic approach and framework to designing, building, deploying and using AI solutions in a responsible and ethical manner so we can accelerate value with confidence. The assessment helps identify change opportunities, creates action plans and sets out a roadmap that benchmarks your progress against industry peers.

      The approach revolves around connecting organisations with emerging technology solutions and leveraging these innovations to help achieve their strategic and business goals. At KPMG, we offer support in navigating regulatory challenges and enhancing efficiency through standardised processes and cloud-based solutions. Our experts bring a deep understanding of risk management, coupled with the innovative digital solutions and specialised guidance you may need to not only meet regulatory requirements but also drive strategic growth and innovation.


      Bent Dalager

      Innovation Lead & Partner, Advisory

      KPMG in Denmark

      AI risk assessment

      Our experts help tailor frameworks designed to embed Trusted AI principles into various stages of your AI initiatives. Risk assessments for single AI/machine learning (ML) algorithms as well as broad assessment reviews of entire AI programs. Development of AI policies and procedures based on principles of integrity, fairness, resilience and explainability.

      AI risk transformation

      We help you ensure accountability throughout the AI lifecycle to integrate trust into your broader machine learning processes. Establish and implement governance, policies, procedures and operating models spanning the AI ecosystem including training, evaluating and continuous monitoring of AI models.

      AI regulations and compliance

      We help you anticipate the impacts of AI regulations and compliance requirements on your AI systems. Conduct detailed checks to align your AI practices with international and industry-specific regulations. Continuous monitoring and updates to keep your AI systems compliant in a rapidly evolving regulatory landscape.



      Ten pillars of KPMG Trusted AI

      • Fairness

        AI solutions should be designed to reduce or eliminate bias against individuals, communities, and groups.

      • Explainability

        AI solutions should be developed and delivered in a way that answers the questions of how and why a conclusion was drawn from the solution.

      • Data integrity

        Data used in AI solutions should be acquired in compliance with applicable laws and regulations and assessed for accuracy, completeness, appropriateness, and quality to drive trusted decisions.

      • Security

        Robust and resilient practices should be implemented to safeguard AI solutions against bad actors, misinformation, or adverse events.

      • Privacy

        AI solutions should be designed to comply with applicable privacy and data protection laws and regulations.

      • Transparency

        AI solutions should include responsible disclosure to provide stakeholders with a clear understanding of what is happening in each solution across the AI lifecycle.

      • Accountability

        Human oversight and responsibility should be embedded across the AI lifecycle to manage risk and comply with applicable laws and regulations.

      • Realiability

        AI solutions should consistently operate in accordance with their intended purpose and scope and at the desired level of precision.
         

      • Safety

        AI solutions should be designed and implemented to safeguard against harm to people, businesses, and property.

      • Sustainability

        AI solutions should be designed to be energy efficient, reduce carbon emissions, and support a cleaner environment.



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