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Autonomous AI agents are everywhere now, and most of them are running without guardrails. A 2025 EMA survey conducted in conjunction with Ory found that 79% of organizations lack written policies for governing AI agents but have already deployed them into production.
Platforms like Ping Identity were built for human federation flows, not for agents that spawn sub-agents, call tools, and need authorization enforced at the exact moment of execution. Ping has added Identity for AI capabilities, so the real question is less about a missing checkbox and more about architecture.
This list compares six Ping Identity alternatives across composable architecture, point-of-execution policy, auditability, and deployability.
How We Evaluated These Platforms
We scored each platform on five criteria, weighted for organizations running autonomous AI agents at scale rather than for general workforce IAM.
- Agent identity architecture: Can it issue unique credentials per agent and sub-agent, and record delegation chains before tools run?
- Point-of-execution authorization: Does authorization happen at the tool-call level, not just at session creation?
- Auditability and observability: Does every action produce an immutable audit record that outlives the token and can be exported to a SIEM?
- Deployability and composability: Can teams self-manage on-premises or in a private cloud? The same EMA survey found 72.1% of organizations prefer self-managed LLM deployment.
- Ecosystem integration: Does it work with the Anthropic Claude Agent SDK, Gemini CLI, OpenAI Codex, Microsoft Agent Framework, MCP, and A2A?
1. Ory: Composable Architecture and Point-of-Execution Enforcement
Ory approaches agent security as a native identity problem rather than a bolt-on. The platform is API-first and composable, so every agent and sub-agent authenticates with its own credentials. Authorization is enforced at the moment an action executes, and the full delegation chain is exported as an audit trail.
- Ory Agent Security authenticates every agent and sub-agent individually, recording the delegation chain before any tool runs. Fine-grained authorization covers shell commands, file writes, MCP tools, and API calls at the point of execution. Ory is one of the few vendors that enforces policy where agents actually execute actions, rather than only at login.
- Every action is exported via OpenTelemetry to the SIEM, and the delegation chain outlives the token. This delivers visibility and observability for Ory-built and connected agents at a forensic level.
- The composable stack maps cleanly to agent identity needs: Ory Hydra for OAuth 2.0 and OIDC, Ory Keto for fine-grained authorization, Ory Talos to transform static API keys into dynamic, short-lived, and scoped machine credentials, and Ory OathKeeper as an identity-aware proxy. Everything runs self-managed, on-premises or in the private cloud, through the Ory Enterprise License, or as a fully managed SaaS platform through the Ory Network.
- Adoption at a massive scale is a strong signal. OpenAI adopted an Ory Enterprise License for Ory Hydra after traditional CIAM fell short on transparency, scalability, and self-hosting. That matters when you consider OpenAI has 1.2 billion weekly users as of September 2026. .
Best for: Teams that need authorization enforced at the tool-call level with a complete observable audit trail, plus organizations that prefer self-managed deployment.
Less ideal if: Your team lacks the engineering bandwidth to assemble a composable stack. If you want an all-in-one turnkey suite with minimal integration work, Ory demands more hands-on configuration.
For organizations where 52.8% want an all-in-one platform but only 24% have achieved it, Ory's composable model offers a practical path without vendor lock-in.
2. Okta (with Auth0): Agent SSO and Tool-Call-Level Authorization
Okta has built a dedicated AI agent stack around Agent SSO, Cross App Access, and fine-grained authorization at the tool-call level. It positions this as a vendor-neutral layer across multi-cloud and SaaS environments.
- Fine-grained authorization at the tool-call level scopes an agent's access to specific actions within an application, with short-lived tokens issued per invocation.
- Agent SSO and Cross App Access let organizations issue short-lived scoped tokens so agents can move across applications without long-lived credentials sitting in configuration files.
- The kill switch revokes an agent's access across connected resources in a single action from the Okta Admin Console, according to a 2026 Okta update. Okta also recommends short-lived tokens, dual-layer on-behalf-of authorization, and immutable audit logs for autonomous agents.
Best for: Organizations already invested in the Okta ecosystem that want to extend their existing IAM fabric to AI agents without adding a separate identity layer.
Less ideal if: You want agent authorization to be self-managed or enforced beyond the Okta control plane, or you need predictable costs. Okta's agent stack is built to extend an existing Okta deployment, and rising or unpredictable costs are the top IAM challenge for 47% of organizations.
Trustpilot reviews, while not representative by Okta's own acknowledgment, also surface end-user friction around login loops and device setup.
For teams that want one identity fabric for humans and agents, Okta is an obvious extension path.
3. Microsoft Entra Agent ID: Native Azure Ecosystem Integration
Microsoft Entra Agent ID extends the Entra identity fabric to AI agents with agent identity blueprints, Conditional Access policies, identity governance, and audit logs. It supports OAuth 2.0, MCP, and A2A, and offers a sidecar Auth SDK for third-party agents.
- Agent identity blueprints provide a templated way to define what an agent is, what it can access, and under what conditions.
- Workload identity federation lets agents authenticate without secrets, while the Auth SDK sidecar wraps third-party agents from AWS Bedrock and n8n with Entra identity controls.
- Full Entra security features for agents require Microsoft Agent 365, tying agent identity into the broader Microsoft governance, privileged access, and SIEM stack.
Best for: Organizations deeply embedded in Azure and Microsoft 365 that want agent identity to flow through the same governance pipeline as workforce identities.
Less ideal if: You operate in multi-cloud environments, where Entra becomes one control plane among many. Practical365 commentary noted that Microsoft's agent licensing is inconsistent, which may complicate budgeting.
For Azure-native teams, this is a streamlined way to bring agent identity under an existing governance umbrella.
4. Aembit: Independent Identity Broker for Agent-to-Service Access
Aembit positions itself as an independent identity broker for AI agents, MCP servers, and workloads. Instead of leaving long-lived credentials in agent configs, it issues short-lived scoped credentials at runtime using a Blended Identity that pairs the agent with the initiating user.
- Blended Identity ties every agent action to both the agent and the human on whose behalf it acts, creating an auditable chain that maps directly to access policy.
- Runtime credential issuance keeps long-lived secrets out of agent configurations and prompt files, with credentials issued only when the agent needs them.
- SOC 2 Type II and ISO/IEC 27001:2022 certification plus a free tier make it easy to evaluate the broker model.
Best for: Teams that want a drop-in identity broker focused specifically on agent-to-service access, without replacing their broader IAM stack.
Less ideal if: You need comprehensive human identity management alongside agent identity. Aembit is a broker, not a full IAM platform, so it complements platforms like Okta or Entra rather than replacing them. Its vendor-landscape guide is instructive, but it comes from a competitor's perspective.
This is a focused, broker-first option for organizations that already have human IAM sorted.
5. Idira (formerly CyberArk): PAM Heritage Meets Agentic Identity
Idira, now part of Palo Alto Networks, combines privileged access management, machine identity, and agentic identity security in one platform. Its May 2026 Identity Security Landscape cites a 109:1 machine-to-human identity ratio and says 99 out of 100 organizations have adopted AI agents.
- The Secure AI Agents module handles agent discovery and provides an identity broker for MCP servers, applying PAM principles like least privilege and just-in-time access to agent interactions.
- Machine identity management covers the broader non-human surface beyond AI agents, including APIs, services, and workloads.
- The Palo Alto Networks acquisition positions Idira inside a wider security platform for organizations that want to consolidate vendors.
Best for: Teams with mature PAM programs and a high ratio of machine identities that want to extend that discipline to AI agents.
Less ideal if: You are building agent-first architectures from scratch. The platform's privileged access heritage may add complexity if that foundation is not already in place.
Idira is about extending existing privileged access discipline to agents, not starting from zero.
6. Teleport: Cryptographic Identity and Ephemeral Access for Agents
Teleport applies its cryptographic identity model, backed by hardware root of trust, to AI agents and MCP tooling. It issues ephemeral just-in-time privileges and extends its identity-aware proxy architecture to agentic workloads.
- Cryptographic identity ties agents to hardware-backed certificates instead of shared secrets, making credential theft significantly harder.
- Ephemeral just-in-time privileges grant access for the exact duration and scope needed, with automatic revocation after the task completes.
- A unified identity layer for humans, machines, and agents keeps access policy in one place rather than spread across separate control planes.
Best for: Infrastructure-focused teams already using Teleport for SSH, Kubernetes, or database access that want to extend the same certificate-based model to AI agents.
Less ideal if: Your primary concern is SaaS application access rather than infrastructure access. Teleport's strengths sit at the infrastructure layer, and broader IAM platforms may feel more feature-complete for API-based agent workflows.
For agent access to infrastructure, Teleport's certificate-based model is a natural fit.
Caveats and Counterpoints
No platform here is turnkey agent IAM in a box. Each requires integration work and organizational commitment.
The 2025 EMA survey found organizations use an average of three IAM platforms, with 34% using four or more, so fragmentation is already the norm.
The same research found 52.8% would prefer an all-in-one platform, but only 24% have achieved it. Most teams stitch components together, and platforms like Ory embrace that reality with composable architecture rather than fighting it.
Cost is also variable. Rising or unpredictable costs top the IAM challenge list at 47%, and 41% report security or reliability concerns with their current providers. Evaluate total cost of ownership, including integration labor, not just licensing fees.
Astrix Security was excluded from this list because it ended standalone new-license sales effective June 30, 2026, following its acquisition by Cisco.
Final Verdict
The agent identity market in 2027 splits into two camps. One group retrofits agent support onto human-first IAM, as Ping Identity, Okta, and Microsoft Entra do. The other treats agents as first-class identity principals from day one, represented by Ory, Aembit, Teleport, and Idira.
For organizations running autonomous AI agents at scale, fine-grained authorization has to happen at the point of execution, and every delegation chain has to be auditable. Composable, API-first architecture aligns with how agents actually operate, and Ory represents that approach most completely.
The 2025 EMA survey found 76% of organizations have deployed tools to identify agents, but only 55% have documented policies to govern them. That gap between identification and governance is where architecture choices matter most.
The right platform depends on your stack, your agent autonomy level, and whether you favor self-managed control or managed-service convenience. Given how fast this space moves, evaluate any option against live agent workloads rather than feature checklists alone.