AI agents are proliferating rapidly across enterprise environments. Every single one requires its own identity, access rights, and governance – just like human users. Most IAM systems aren’t ready for this. Trivore is.
Traditional identity management was built for humans: employees, contractors, and partners. However, in the modern organisation, the majority of identities are non-human. Service accounts, API keys, automations, IoT devices, and now AI agents make up the bulk of identities – and their numbers are skyrocketing.
Most IAM systems fail to distinguish between humans, machines, and agents. Everything is forced into the same management model, using the same processes and constraints. The result: machine identities are often unmanaged and over-privileged.
Modern identity management requires the recognition and governance of six distinct identity types. Each has its own lifecycle, risk profile, and management model.
Employees, contractors, and temporary staff. One person, one identity. Lifecycle tied to employment.
Governance through roles and tasks
Team accounts, administrative mailboxes, shared accounts. Used by people, but not tied to one person.
Risk: lack of accountability
AI tools that act on behalf of humans: assistants, copilots, automation. Rights are derived from user rights.
Never more rights than the user
Autonomous AI systems: customer service bots, security monitors, workflow orchestrators. Own identity and lifecycle.
Needs its own governance model
Application integrations, IoT and OT devices, CI/CD pipes, API connections. A rapidly growing non-human layer.
Often unmanaged and over-privileged.
Partner systems, B2B connections, third-party AI agents. You don’t control identity, but you must manage its access.
Trust boundaries between organisations
Trivore builds non-human identity management into the core of the platform – not as a separate add-on or a workaround. All six identity types are governed under a single architecture.
Trivore’s identity model already supports the creation of non-human identities with their own roles and permissions. Humans and agents are managed in one place.
All six identity categories as a structural part of the platform. Different types have different processes, governance models, and pricing.
When a human works through an AI agent, the agent only gets the rights needed to do the job – never more than a human would have.
Different identities carry different risks and require different lifecycle management. Trivore applies specific rules to each, from onboarding and auditing to decommissioning.
As AI agents become more common, the criteria for selecting an IAM solution will change. These questions will help you assess whether your solution is ready for the future.
Machine and AI agent identities should be first-class citizens of the system – not a workaround or an add-on.
When humans act through an AI agent, the system should automatically limit the agent’s access – not rely on manual configuration.
Different types of identity have different life cycles and access needs. An IAM solution should reflect this, not force everything into the same mould.
You need to know what each identity did, when, with what rights – and for delegated agents, on whose behalf. A single log file that mixes human, machine, and AI activity is not enough.
The field of identity is expanding rapidly. A solution that dominates today’s categories but does not adapt to new ones will need to be replaced sooner than expected.
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