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Headwinds Persist for AI-driven Data Collection and Asset Visibility
Using AI for Risk Reduction Offers Significant Advantages
The SOC Analyst Must Adapt to a Changing Role
Trust Is Required to Grow AI Adoption
Conclusion
Research Methodology
Respondent Demographics
Research Report: Automating Risk Reduction in the AI Era
Research Report
Dec 24, 2025
by
Tyler Shields, Emily Marsh
Cybersecurity and asset context are accessible programmatically, allowing API-based data collection and AI-backed security data analysis to operate continuously. As offensive threats take advantage of similar capabilities, cybersecurity professionals cannot allow themselves to become outpaced in the AI arms race. The threat landscape and enterprise cyber asset counts are growing exponentially, requiring AI to keep up with the pace of growth.
How are organizations adapting their approaches to tools and processes when it comes to AI-driven risk and threat discovery, prioritization, and remediation?
To answer that question and gain further insight into these trends, Omdia surveyed 400 IT and cybersecurity professionals at organizations in North America (U.S. and Canada) involved with or responsible for evaluating and purchasing security risk management technology products and services.
Page Count: 24
Table of Contents
Executive Summary
Report Conclusions
Introduction
Research Objectives
Research Findings
Headwinds Persist for AI-driven Data Collection and Asset Visibility
Using AI for Risk Reduction Offers Significant Advantages
