IARM specializes in providing comprehensive AI Model risk management services designed to meet the unique needs of businesses navigating the complexities of AI adoption. With our in-depth understanding of AI security best practices and regulatory requirements, we partner with clients to assess, identify, and address risks and vulnerabilities throughout the AI lifecycle. Our goal is to empower businesses to leverage the transformative power of AI Models with confidence, knowing that their systems are protected against evolving cyber threats.

Perform a Gap Assessment to identify the level of Governance structure and Policy that exists in the organization. Work closely with clients to determine the appropriate risk management framework based on their specific business needs and regulatory requirements.

Draft an Artificial Intelligence Governance Policy that outlines the organizations principles and guidelines for the development, deployment, and use of AI. The policy shall cover the principles of AI including Accountability, Transparency, Fairness, Non-discrimination, Privacy, and Security. Provide a comprehensive AI Governance Structure which defines the roles and responsibilities of different stakeholders involved in AI governance, such as the AI governance committee, data protection officer, and AI developers, among others.

Conduct a comprehensive security risk assessment using industry-standard methodologies such as the NIST Framework / ISO 42001:2023 Standard to assess the potential risks associated with the AI Model system, such as bias, discrimination, privacy breaches, and security vulnerabilities.

Draft a Risk Management plan that outlines the strategies and controls to mitigate the identified risks associated with the AI system. Based on the Risk Management plan and Risk assessment exercise, draft a detailed report outlining identified vulnerabilities and security risks specifically related to the AI system, its development environment, data storage, and usage *(Reference: ISO 42001:2023/NIST Cybersecurity Framework)*

Consult and collaborate with the client to implement a secure development lifecycle specific to AI development, including training developers on the importance of systematic security evaluation and integrating security practices into their workflow.

Document best practices for secure development lifecycle processes tailored to the clients AI development practices, encompassing secure coding practices, threat modeling, and secure software deployment procedures

Conduct data security and privacy assessments, assist with data management plan development, and offer guidance on implementing data security controls and privacy-enhancing techniques

A Compliance Audit Report shall report the results of an audit conducted to assess the AI Model Risk systems compliance with relevant regulations and standards (e.g., GDPR AI Act, HIPAA), along with recommendations for compliance AI Security Awareness Training:

Provide training programs for the clients personnel on AI-specific security risks and best practices based on NIST and ISO/IEC 42001:2023 Framework & Best Practices Standards.