AI Governance

What is the Centraleyes AI Governance Framework?

The AI Governance assessment, created by the Analyst Team at Centraleyes, is designed to fill a critical gap for organizations that use pre-made or built-in AI tools. While many official assessments focus on helping developers secure AI systems, our assessment provides a tailored approach for users of these AI technologies, as well as in-house developers. It helps organizations ensure their AI tools are secure, compliant with regulations, and used ethically. By identifying and mitigating security vulnerabilities, implementing robust controls, and preparing for potential threats, this assessment empowers organizations to confidently leverage AI technologies while protecting their data and maintaining trust. The AI Governance assessment is a highly valuable tool to enhance AI governance and risk management practices within the organization.

The development of this framework drew upon various reputable sources, including consideration of the OWASP AI Security and Privacy Guide, CISA’s “Deploying AI Systems Securely” publication, as well as AI framework requirements outlined by NIST and ISO. Additionally, it benefited from extensive experience and research within the AI field. Relevant to a diverse range of industries and functions, the AI Governance assessment framework addresses the ethical, legal, and security considerations associated with AI deployment. In an ever-evolving landscape, this framework undergoes regular revisions to incorporate emerging risks, regulatory requirements, and advancements in AI technology, ensuring its continued relevance and effectiveness.

What are the requirements for AI Governance?

Describe what are the prerequisites and steps you need to take in order to comply with the framework or submit an application. What are the basic requirements from an organization? What are actionable steps an organization needs to take? Are there any specific controls or related standards that go hand in hand with or complement this framework? Who is the authorizing/approving/qualifying body/organization?

The primary goals of the AI Governance assessment are threefold. Firstly, it aims to enhance the confidentiality, integrity, and availability of AI systems by striving to implement robust security measures that safeguard sensitive data, ensure the accuracy of AI algorithms, and maintain the availability of AI services. Secondly, the assessment seeks to assure that known cybersecurity vulnerabilities inherent in AI systems are acknowledged and addressed effectively. By conducting thorough vulnerability assessments and implementing appropriate risk mitigation strategies, organizations can work towards strengthening the overall security posture of their AI infrastructure. Lastly, the assessment aims to provide methodologies and controls to protect, detect, and respond to potential malicious activities targeting AI systems and associated data and services. This involves the implementation of proactive measures such as intrusion detection systems, access controls, encryption mechanisms, and incident response procedures tailored specifically to the unique characteristics and challenges of AI technology. Through these efforts, organizations aim to mitigate risks and ensure the security and resilience of their AI ecosystems.

Users of the assessment will be required to assess 5 foundational areas:

Governance & Accountability

Compliance & Legal

Data Security & Privacy

Model Security & Integrity

Incident Response & Monitoring

The assessment empowers security teams with both a high-level and more granular view of their position.

Why should you use the AI Governance security assessment?

Using the AI Governance security assessment helps your organization to confidently navigate the complexities of AI technology. It provides a structured approach to identify, mitigate, and manage risks associated with AI systems, enhancing data security, regulatory compliance, and ethical use. By leveraging this assessment, you can safeguard sensitive information, mitigate cybersecurity threats, and build trust with stakeholders, ultimately optimizing the responsible deployment of AI within your organization.

Using the AI Governance security assessment complements existing frameworks such as those from NIST and ISO, offering a tailored approach specifically focused on the unique challenges of AI systems. It enhances the comprehensive evaluation of AI-related risks, aligning with industry standards while providing actionable insights to address vulnerabilities effectively. By integrating this assessment into your organization’s existing risk management practices, you can ensure a more holistic approach to securing AI technologies and bolstering overall cybersecurity posture.

How to achieve compliance?

Achieving compliance with the AI Governance security assessment involves a systematic approach facilitated by Centraleyes Risk & Compliance Management platform.

Organizations begin by understanding their AI landscape and setting clear guidelines for its utilization, fostering alignment and commitment from leadership. In the planning phase, potential risks are anticipated, and objectives for AI systems are established, supported by adequate resources, training, and communication channels. Centraleyes streamlines this process through its cloud-native platform, automating risk management tasks from data collection to analysis and remediation. Its intuitive interfaces and smart questionnaires enable efficient risk assessments, while the automated Risk Register provides detailed risk information tailored to organizational data. Centraleyes’ automated ticketing process facilitates seamless task management, delegation, and tracking, ensuring accountability and swift results.

By integrating Centraleyes into their AI governance framework, organizations can achieve compliance, cyber resilience, and continuous improvement in their AI operations, positioning themselves for effective utilization of AI technologies in a secure and responsible manner.
Read more:The Importance of AI Governance Standards in GRC

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