You cannot govern — or stop paying for — what you cannot see. A spreadsheet of approved tools is out of date the moment it's saved.
Shadow IT identification means continuously discovering every IT asset running, or idle, across every cloud and on-prem platform across your enterprise -- sanctioned or not, active, failed, obsolete, forgotten -- so you can cut redundant spend, close data-exposure risk, and route each finding to approve, replace, or retire, instead of relying on an outdated spreadsheet.
Forgotten, obsolete, legacy, failed hardware not decommissioned and removed from service is a redundant cost the CTO should not be spending. Further, with AI now in the mix, they remain a potentially unknown, unmanaged risk surface, just waiting for the right bad actor. AI and SaaS tools arrive faster than governance can track them: personal accounts, browser-based tools, AI features quietly switched on inside existing platforms, and unofficial agents or code assistants. Each one is both an unmanaged cost and an unmanaged risk — sensitive data can move through a tool no one approved, budgeted, or is monitoring.
AAOOMI's recommended partner capability surfaces shadow IT automatically across all cloud and on-prem platforms, models, applications, agents, browsers, and SaaS — without endpoint agents or new network plumbing. It reads the cloud and SIEM logs you already run (AWS, Azure, Google Cloud, Splunk, Sentinel, QRadar, Elastic, CrowdStrike, Datadog, and others) and builds a living, continuously updated inventory of every hardware device, tool, model, and provider in use, attributed to the teams and applications running it.
Findings are risk-scored by data sensitivity and decision impact, so a low-risk personal research tool is separated from an unofficial tool drafting advice on confidential documents. Every finding routes into a clear action: approve what's low-risk and useful, replace personal accounts with a sanctioned tool, bring valuable-but-risky usage under runtime control, or retire what's genuinely dangerous — turning a discovery exercise directly into cost recovery and risk reduction.
In financial services, this closes cost and evidence gaps across trading desks and fraud-prevention tooling. In healthcare and HCM environments, it brings clinical, administrative, and workforce tool usage into a single current view — before an errant server or personal-account habit becomes a HIPAA or data-privacy incident.
Shadow IT is any tool, app, or AI service used inside an organization without formal approval — personal ChatGPT accounts, unsanctioned browser extensions, or AI features quietly switched on inside existing SaaS platforms are common examples.
Modern discovery tools read logs you already generate — cloud platforms (AWS, Azure, GCP) and SIEM/log sources (Splunk, Sentinel, QRadar, and others) — rather than requiring new endpoint software or network changes.
Yes — discovery routinely surfaces duplicate or redundant tool subscriptions across teams. Consolidating those into sanctioned, negotiated tools is typically the fastest-payback step in a shadow IT program.
Schedule time directly with our Axonyx partner contact to scope a shadow AI and shadow IT exposure review.