Axonius AI Workforce

• Getting a ranked morning briefing of what changed overnight, such as how many open findings now clear your ticketing policy, without building reports
• Letting a worker preview the tickets or cases it would create in Human in the loop mode, then approving or declining them before anything reaches the ticketing system
• Tracking unsanctioned AI use in the environment with a Shadow AI worker
• Following post-quantum cryptography readiness over time with the Post-Quantum Cryptography Readiness worker's headline metric
• Writing a custom worker that runs after a specific adapter fetch, checks for a condition you describe in its prompt, and previews cases or tickets for the matching assets
• Spotting gaps in asset data with a Data Completeness worker

AI Workforce is the clearest case in this list of an agent whose value comes from the data it sits on rather than the model. If Axonius already ingests most of your tools, you get dozens of workers that start reporting after the first discovery cycle and can draft the tickets, cases and tags that usually wait for an analyst; if it does not, many workers sit in Set up waiting for an adapter or module. The control model is more granular than most security agents: modes per action, a write cap per run, a final approval card in chat, and actions that can never be automated. Start with Human in the loop, see which proposals your team approves without edits, and move only those actions to Live. Evaluate it as part of an Axonius purchase or renewal, not as a separate tool, and get the credit terms in writing, since the documentation describes expiring buckets and a free trial period for automated runs that may change.

About Axonius AI Workforce

Axonius sells a cyber asset and exposure management platform that pulls device, user, software, cloud and vulnerability data from the tools a company already runs (Axonius cites more than 1,400 bidirectional integrations) and reconciles it into one inventory. AI Workforce, generally available since October 19, 2026 alongside the AI Companion chat and the Axonius MCP Server, puts agents on top of that inventory. Axonius ships more than 50 Virtual Worker types, grouped into departments such as Vulnerability Management, Endpoint Security and Identity & Access Management, each with a typical owner role. A built-in AI Workforce account runs each enabled worker after every discovery cycle, so briefings start arriving after the first completed cycle without anyone writing a query or a scheduled report. Each briefing leads with a headline metric and how it moved since the last run, then a summary, the actions the worker took or previewed, and suggested next steps; a Daily Digest ranks the most urgent findings on the AI Workforce homepage. A worker becomes active only when its inputs exist: the right adapter is connected (CMDB workers need ServiceNow, for example), a module such as Exposures is enabled, or the data is in the inventory. Control is set per action. Each write a worker can make, such as Create Ticket, Create Case, Run Enforcement or Run Workflow, is set to Off, Human in the loop (preview and wait for approval) or Live (apply automatically), with a recommended starting mode and a cap on writes per run (10 by default). The launch announcement calls these modes Off, Shadow and Live. Changes approved from a notification still pass through a final approval card in the chat, high-risk actions such as user and role management can never be automated, and every action is logged as agent-driven or human-driven. Teams can also write custom workers from a prompt of up to 2,000 characters on a schedule or an event trigger. The tradeoffs: it only exists inside an Axonius deployment, and only the Axonius-hosted SaaS version; its usefulness depends on how much of your environment Axonius already ingests; it runs on Anthropic models in a private instance per customer rather than a model you choose; and usage is metered in AI credits, while Axonius publishes no prices for the platform or credits.