Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

‍ ‍Kovrr, a global leader in cyber and AI risk management, today announced the launch of its AI Security Risk Governance suite, a comprehensive solution developed to help enterprises at any phase of adoption harness the value of GenAI responsibly.

‍General-purpose AI (GenAI) and other artificial intelligence (AI) systems are now completely embedded within business processes across the market. The once purely imagined technology is significantly influencing operations and reshaping the very processes under which high-level decisions are made.

‍Conducting a risk assessment has become a baseline requirement, not merely an internal best practice, for building effective GRC programs. Whether their focus is on cybersecurity or the newer frontier of AI, assessments offer a systematic means of illuminating an organization’s current exposure and providing visibility into how safeguards are working across both domains. For many teams, however, beginning the assessment remains a challenge.

‍ Artificial intelligence (AI) used to be something that only existed in science fiction novels and dystopian movies. Then, technology advanced, and it became a reality, being slowly implemented into experimental projects and niche use cases. Now, however, it is shaping real business outcomes, accelerating decisions and automating processes in ways that are becoming commonplace in daily market operations. ‍

‍Artificial intelligence (AI) has departed from the realm of science fiction and emerged as a very real, regular part of life, increasing efficiency across a number of everyday activities. Particularly in the marketplace, where process optimization directly equates to time and money, general-purpose AI (GenAI) and other AI systems have rapidly taken on a central role.

Most organizations have invested in their cybersecurity programs, ensuring that targeted actions have been taken, such as the deployment of security tools or the formalization of cyber-relevant policies, to reduce their exposure.

‍ ‍Cyber risk quantification (CRQ) is the process of attributing numerical values to a cyber event's impact on an organization. When defined in financial terms, these values enable enterprises to assess and manage their cyber risks at the operational level.

‍Cyber risk quantification (CRQ) is the process of translating cyber intelligence, both organization-specific and external, into measurable business terms. Typical high-level outputs include Average Annual Loss (AAL), or a business's expected financial loss from cyber events, and the Annual Events Likelihood. With CRQ, cyber governance, risk, and compliance (GRC) leaders can also drill down into more granular metrics for additional, scenario-specific context.

‍ ‍With the continuously expanding influence that cybersecurity has in determining an organization's financial and operational resilience, cyber risk quantification (CRQ) has steadily become a foundational component of any robust cyber governance, risk, and compliance (GRC) program.

‍ ‍Risk managers have long used registers to keep track of and manage the threats their organizations face, and, as cyber risk emerged in the 21st century as one of the core market concerns, cybersecurity leaders, too, started to harness these tools to structure and prioritize their cyber-related exposure. However, while risk registers offer a starting point for this process, many have not evolved beyond their early design, remaining static qualitative inventories.