How AI assessments can enhance confidence in AI

Understanding the AI assessment landscape

As of January 2025, policymakers from nearly 70 countries have introduced over a thousand AI public policy initiatives, including legislation, regulation, voluntary initiatives and agreements, according to the Organisation for Economic Co-operation and Development (OECD). Many of these initiatives include various types of AI assessments.  These assessments can be broadly grouped into three categories:
 

1. Governance assessments, which determine whether appropriate internal corporate governance policies, processes and personnel are in place to manage an AI system, including that system’s risks, suitability and reliability.
   
   
2. Conformity assessments, which determine whether an organization’s AI system complies with relevant laws, regulations, standards or other policy requirements.
   
   
3. Performance assessments, which measure the quality of performance of an AI systems’ core functions, such as accuracy, non-discrimination and reliability. They often use quantitative metrics to assess specific aspects of the AI system.
    

Even with these three emerging types of assessments, there can be significant variations in assessment quality. To address these shortcomings, we recommend that all AI assessments include the following characteristics:
 

• Specificity about what is to be assessed and why: An effective AI assessment framework will have a clearly specified and articulated business or policy objective, scope and subject matter.
  
  
• Clear methodology: Methodologies and suitable criteria determine how a subject matter is assessed, and it is essential that similar AI assessments use clearly defined and consistent approaches. Some assessments, for instance, may include explicit opinions or conclusions, while others may only provide a summary of procedures performed. Consistency, combined with clear terminology, allows users to compare assessment outcomes and understand how they were reached.
  
  
• Suitable qualifications for those providing the assessment: The choice of assessment provider is crucial and directly influences the credibility, reliability and overall integrity of the process. Key considerations for selecting assessment providers include competency and qualifications, objectivity and professional accountability.

Next steps for business leaders

• Consider the role AI assessments can play in enhancing corporate governance and risk management. AI assessments can help business leaders identify and manage evolving risks associated with their AI systems and help indicate whether AI systems perform as intended.
  
  
• Evaluate whether – even in the absence of any regulatory obligations – to conduct voluntary assessments to build confidence in AI systems among employees, customers and other important stakeholders. Market dynamics, investor demand or internal governance considerations may make a voluntary AI assessment advisable to build confidence in a business’s AI systems. Moreover, if some AI systems are subject to regulatory obligations, business leaders may choose to use assessments to help measure and monitor compliance.
  
  
• Where voluntary assessments are used, determine the most appropriate assessment. Business leaders will want to determine whether to conduct a governance, compliance and performance assessment, and whether it should be conducted internally or by a third party.