Cybersecurity today is more than an IT issue — it’s a core business risk affecting revenue, operations, reputation, and competitiveness. Yet most organizations still rely on subjective approaches, using gut instinct or limited data, often missing threats hidden in data silos, shadow IT, outdated software, or supply chain vulnerabilities.
Is moving past intuition too disruptive? Not at all. Even with legacy systems and data silos, the shift to objective, data-driven risk management is achievable. According to a recent Ivanti survey of 2,400 cybersecurity professionals, common blockers — such as limited visibility and persistent end-of-life (EOL) software — are widespread but not insurmountable:
- 55% face data silos.
- 45% struggle to detect shadow IT.
- 43% can’t spot supply chain vulnerabilities.
- 48% rely on EOL software, especially in healthcare.
The good news: Organizations don’t need a massive overhaul. With structured frameworks, AI-powered analytics, and stepwise guidance, even incremental changes deliver real value. Moving to objective evaluation brings faster decisions, clearer priorities, and measurable resilience — without unnecessary hassle.
Common roadblocks — and the way forward
Nearly all organizations hit obstacles in their journey to effective risk assessment. It’s easy to default to incomplete information, especially when teams are stretched and data is scattered. Subjective approaches — albeit common — often miss hidden risks such as unmanaged shadow IT or outdated assets. Recognizing these pitfalls is the first step toward overcoming them.
Objective evaluation, powered by exposure management platforms, brings together enterprise-wide data, contextualizes risks by real business impact, and applies structured frameworks and AI analytics for measurable results. Still, only half of organizations rigorously apply their risk tolerance frameworks — often hindered by data access limitations and talent shortages.
Steps to modernize your cyber risk approach
Ivanti’s Exposure Management Strategy Guide offers practical next steps:
- Inventory cybersecurity tools, and use readiness checklists.
- Assign asset criticality scores with internal data.
- Prioritize vulnerabilities by risk exposure scores — merging likelihood and impact.
- Perform cost/benefit analysis on mitigation versus risk acceptance.
- Review risks and controls to adapt over time.
Metrics that matter
IT teams can modernize risk evaluation by using metrics such as:
- Asset criticality scores: Evaluate assets by business value.
- Vulnerability exploitation likelihood: Focus remediation on high-likelihood threats.
- Risk exposure scores: Combine likelihood with impact, aligning with risk frameworks.
- Time for detection and response: Shorten response times — 62% said siloed data slows them down.
- EOL software usage rate: Track and reduce outdated assets, especially in high-risk sectors.
- Data silo integration progress: Measure visibility gains across IT and Security.
How artificial intelligence (AI) drives smarter risk decisions
Generative and agentic AI have distinct roles:
- Generative AI synthesizes vulnerability and threat data, creates business context reports, and produces risk framework templates.
- Agentic AI automates inventory, prioritization, and ongoing risk scoring, detecting assets in shadow IT and cloud environments. Human oversight is crucial for validating outputs and setting thresholds.
Inside Ivanti’s exposure management platform
Ivanti’s suite (Ivanti Neurons for risk-based vulnerability management (RBVM), external attack surface management (EASM), and patch management) provides:
- Continuous discovery and prioritization based on impact and likelihood
- Automated external exposure identification — shadow IT, cloud, third-party risk
- Data aggregation across endpoints, networks, software as a service (SaaS)
- Seamless patch management integration
- Cross-functional collaboration tools
Results include shorter response times, fewer blind spots, and improved objective metrics. Ivanti’s platform users saw a 14-point year-over-year improvement in data integration.
“Moving from gut feel to data-driven cyber risk decisions does more than tighten up security — it helps businesses adapt and stay ahead,” says Karl Triebes, chief product officer at Ivanti. “When you really understand your risks, you can invest smarter; tackle threats faster; and build a stronger, more resilient company.”
Your action plan for measurable cybersecurity
Cybersecurity as a strategic business enabler
Organizations that embrace objective, data-driven cyber risk evaluation gain resilience, informed allocation, and a long-term competitive edge. With the right tools, cybersecurity transforms from cost center to business enabler.
Learn more about how Ivanti can help your organization adopt an objective approach to managing and measuring cybersecurity risk.
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