AI Risk Management

What is AI risk management?

AI risk management uses AI to score, prioritize and respond to cyber and business risk. In DigitalXForce, AI scoring rates every risk by likelihood and impact in the register of the Enterprise Risk Management module. X-ROC, the XForce Risk Operations Center, is the operations layer of the DigitalXForce TRiSCM platform, where control failures, risk changes and vendor events are alerted, triaged, escalated and reported.

Is AI risk management the same as AI governance?

AI risk management, as this page uses the term, applies AI to the cyber and business risks an organization already carries. AI governance is the set of policies, roles, controls and evidence an organization uses to decide which AI systems it runs, how they may be used and whether their controls keep working. DigitalXForce covers AI governance in the AI TRiSCM and AI Risk Governance module, and the risks that module finds go into the same enterprise risk register.

How does AI score a risk in DigitalXForce?

AI JedAI scores and prioritizes each risk in the DigitalXForce register using impact and likelihood scales that each organization configures for itself. AI JedAI is the DigitalXForce AI engine that analyzes: it reasons over control evidence and live telemetry, maps documents to controls and frameworks, scores and prioritizes risk, and recommends remediation mapped to framework requirements. Each risk in the enterprise risk register gets inherent and residual scores and a treatment.

How does DigitalXForce rank risk by business impact?

X-ROC triage ranks alerts by quantified business impact, using cyber risk quantification, not by a severity label alone. Cyber risk quantification (CRQ) quantifies a cyber risk in dollars, giving the financial loss the organization would face if the risk materializes. DigitalXForce uses its own model for CRQ, built on industry best practices and the data the platform collects. These dollar amounts are model estimates for ranking risk, and they should not be read as accounting numbers.

Where do the control failures that X-ROC triages come from?

X-ROC receives its control failures from Continuous Control Assurance. Continuous Control Assurance (CCA) uses evidence, monitoring and validation to determine whether controls continue to operate as expected. Continuous Control Monitoring (CCM) monitors conditions, evidence and signals associated with controls, and it works as a capability within CCA. Each failure reaches X-ROC with the test result and the evidence attached, in the same queue as posture changes and vendor events.

Does the AI act on its own?

X-ROC never changes a customer’s systems on its own. AI JedAI recommends remediation mapped to framework requirements, the team that owns the system makes the fix, and X-ROC tracks the work to closure. An analyst checks the AI output before the team uses it, and the organization’s own people choose how to treat each risk.

How does AI risk management reach executives and the board?

XForce GPT writes the narrative for an executive reader from the same data, covering what changed, what it could cost and what was done. XForce GPT is the DigitalXForce generative AI engine that writes: it produces the plain-language risk narratives and board-ready reports, generates policies, standards and plans, and runs the embedded assistant. X-ROC provides dashboards for the CISO, the CIO and the board. The board cyber risk reporting page shows the chain from a failed control to the trend the board sees.