Platform updates introduce AI-driven risk resolution and expanded visibility for medical devices and internet-connected equipment.
Axonius announced an expansion of its asset intelligence platform, introducing artificial intelligence (AI)-powered remediation and extending coverage to cyber-physical environments, including medical devices.
The expansion includes new capabilities for exposure management, the integration of internet of things (IoT) and operational technology (OT) environments, and a new standard for asset data verification. These tools are designed to address gaps in how organizations track, prioritize, and fix security vulnerabilities.
“Security environments have grown more distributed, more dynamic, and more complex, and when teams can’t fully understand their environment, they simply cannot act,” says Joe Diamond, president and interim CEO of Axonius, in a release. “Findings pile up because the data isn’t trusted, ownership isn’t clear, and entire asset classes aren’t even in the picture.”
Addressing the Actionability Gap
The updates follow the release of the Axonius 2026 Actionability Report, conducted with the Ponemon Institute. The survey of 662 IT and security professionals found that only 45% of organizations consolidate assets and exposures into a single view, while 55% still track remediation in spreadsheets.
The report also noted that while teams agree that business impact should drive how they prioritize risks, only 23% always apply that context. Furthermore, only about half of organizations consistently assign ownership when identifying a security exposure, with more than a third relying on manual workflows.
AI-Driven Risk Resolution
The updated platform uses AI to suggest specific remediation and mitigation steps for security findings, which are ranked by expected impact. This includes attack-path analysis to prioritize containment based on actual exploitability rather than isolated severity scores.
The system also automates the assignment of remediation ownership by using business and organizational context to identify the appropriate staff member for each task. This is intended to reduce the time between identifying a risk and resolving it.
“The real challenge is closing the gap between detection and remediation at scale,” says Francis Odum, founder and head analyst at Software Analyst Cyber Research, in a release. “When you combine reliable asset context with AI that can reason about what to fix and who should fix it, you start to see exposure management shift from a dashboard exercise to an operational discipline.”
Focus on Cyber-Physical and Medical Assets
Following the acquisition of Cynerio in 2025, the platform now incorporates discovery and protection for cyber-physical assets. This technology was first utilized in healthcare settings, where critical medical devices coexist with traditional information technology (IT) systems and where security disruptions can lead to significant consequences.
The platform identifies and fingerprints these devices, correlating them with IT assets to provide unified visibility. This allows organizations to prioritize risks based on operational impact and business criticality, incorporating device dependencies and enriched risk context.
To support these automated workflows, a new verification feature continuously evaluates asset records against multiple trust signals. This distinguishes verified records from duplicates or stale data, providing an audit-ready inventory for security decisions.
Core capabilities for risk scoring and status management are available now, while AI-driven remediation and cyber-physical asset support are expected to reach general availability in the second half of 2026.
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