Start Adding Your First AI Risk Scenarios

AI risk only becomes manageable once it’s properly documented, structured, and owned. Kovrr’s AI Risk Register ensures you can begin this process with ease. Sign up today and capture your first five AI risk scenarios in an intuitive, SaaS-based register and discover how simple it becomes to keep track of risks and build mitigation plans.

Turn Scattered AI Concerns Into Structured Risk Records

Most AI risk is outlined in conversations or spreadsheets, making prioritization unclear and accountability harder than it needs to be. The AI Risk Register offers a single place to document what could go wrong, understand potential impact, and track how each risk is managed. See how a structured register takes shape in practice for free.

Dashboard for real-time payment fraud detection failure showing risk priority as critical, impact severe, likelihood expected, financial loss of 2.4 million USD, and data exposure details.
Dashboard showing a security risk named Real-Time Payment Fraud Detection Failure with severe impact, expected likelihood, 15% annual event likelihood, and 2.40M USD average financial loss.

What Happens When You Add an AI Loss Scenario

Instead of writing notes in isolation, you build a complete view of the risk in one interface. You can define the type of AI risk, set qualitative impact and likelihood, and add quantitative metrics that reflect potential loss or frequency. The result is a risk entry that holds context, assumptions, and analysis together, without relying on spreadsheets.

Progress From Identification to Management

Once a scenario exists, the register supports active risk management.You can link affected assets, document how the risk could be triggered, and categorize the event and impact types involved. Ownership and status are visible at a glance, so it’s clear who is responsible. Nothing gets lost between tools, and progress doesn’t rely on memory or manual tracking.

Risk management interface showing a critical risk priority with details on initial access tactics, cyber event types, impact types, risk subcategories, and a response plan.
UI panel titled Relevant Controls with sections for Current Controls showing three items including legal requirements and risk management processes, and Planned Controls.

Connect AI Risks to Controls and Evidence

Each scenario can be tied to relevant controls, creating traceability between identified risks and the safeguards intended to address them. This alignment helps explain how risks are mitigated, not just that they exist. Notes and attachments keep supporting context close at hand. Whether it’s documentation or supporting analysis, everything stays connected to the scenario.

Why Start Adding Five AI Loss Scenarios?

You don’t need a full register to understand the value of structure. By the time five scenarios are added, patterns emerge. Priorities become clearer. Gaps in ownership or mitigation stand out. This experience is intentionally limited so you can focus on learning the workflow, seeing how risks are captured, and deciding how you want to manage AI exposure.

Two businessmen in suits reviewing a document together at a desk
Every AI Related Loss Is Capturedin One Risk Record
Each AI risk scenario you create is stored as a single, structured entry. Every detail stays visible and easy to manage as the scenario evolves.
Scenario
Description

Define what could go wrong and why it matters in clear, business-relevant terms.

Qualitative Metrics

Set impact and likelihood using consistent severity scales.

Quantitative Metrics

Record estimated financial loss and frequency to support prioritization.

Data
Exposure

Document affected data types and record volumes tied to the scenario.

Risk
Priority

See how severity and likelihood combine to surface what demands attention.

Affected
Assets

Link systems, models, or processes involved in the risk.

Cyber Event
Type

Classify how the scenario materializes, from integrity failures to data misuse.

Impact
Type

Capture financial, regulatory, operational, or reputational consequences.

Risk
Owner

Assign clear accountability for oversight and response.

Status

Track whether the risk is identified, under review, or actively managed.

Response
Plan

Document the chosen approach, including mitigation or acceptance.

Tickets

Connect operational work items directly to the risk record.

Review
Date

Set checkpoints to revisit assumptions and progress.

Mitigation
Costs

Record the investment required to reduce or manage exposure.

Relevant
Controls

Tie the scenario to safeguards intended to mitigate it.

Notes and Attachments

Keep supporting context, decisions, and evidence in one place.

Turn Your AI Risks Into Something You Can Manage

Add real AI risks using a structured register designed for active oversight. Capture context in one place and see how governance takes shape as scenarios accumulate.