AI Applied Radar: AI Applied To Risk Management
Katelyn Johnson
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Executive Summary
This report delivers a comprehensive assessment of AI-augmented use cases for risk management, enabling risk managers to assess each use case’s trustworthiness, business value and operational viability. The AI Applied Radar analysis evaluates a spectrum of AI-driven solutions, using a methodology grounded in expert interviews, global surveys and technical review. This report maps each use case across mainstream, pilot and emerging phases of market adoption. Mainstream deployments encompass compliance assistants, third-party risk scoring and triage, and automatic policy and controls mapping. Pilots target real-time alerts, novel threat analysis and process intelligent task completion. Emerging concepts, such as machine learning (ML) combined with physics-based modelling for faster climate risk assessments and supplier performance prediction models, remain developer-focused. The Radar provides actionable insights for risk managers and vendors seeking scalable, high-impact AI adoption.About the Authors
Mahum Khawar
Analyst
Mahum is an Analyst at Verdantix, specializing in AI integrations within risk management software and operational resilience. She advises technology buyers and software vendor...
View ProfileKatelyn Johnson
Senior Manager
Katelyn is a Senior Manager at Verdantix, specializing in enterprise risk management and external risk and resilience. She helps executives navigate today’s evolving ris...
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