Best Agentic Identity and Security (AISP) Platforms

Agentic Identity and Security (AISP) Platforms Guide

Agentic Identity and Security Platforms (AISP) are emerging as a critical new class of enterprise technology designed to govern and protect the identities, actions, and privileges of AI-driven agents and “digital workers.” These agents operate autonomously within cloud, SaaS, and hybrid systems, often performing complex workflows, making decisions, and triggering actions without direct human intervention. Traditional identity and access management (IAM) and security frameworks were built for human users and static services, but they struggle to address the dynamic, context-sensitive behaviors, scale and autonomy of agentic systems.

Because AI agents can dynamically discover tools, adapt their behavior, coordinate with other agents and act at machine speed, they introduce a unique “access-trust gap” where what they can do may far exceed what they should be allowed to do.

An AISP provides the real-time policy enforcement, least-privilege access, identity attribution, governance, and auditability required to ensure that autonomous agents operate within safe and compliant boundaries. Key capabilities of an AISP typically include agent identity & access management, data and knowledge protection, operational integrity/resilience, agentic governance/risk/compliance, runtime policy enforcement, and human oversight & attribution.

From a strategic perspective, the market for AISP is projected to grow significantly, reflecting the increasing adoption of agentic AI by enterprises and the accompanying security risks. Analysts at Aragon Research forecast the AISP market will climb from around US $3.2 billion in 2025 to about US $32.9 billion by 2031.

For organizations deploying AI agents at scale, integrating an AISP isn’t simply a “nice-to-have” but is becoming an imperative to secure their enterprise, ensure governance, manage non-human identities and close the emergent access-trust gap presented by autonomous systems.

Agentic Identity and Security (AISP) Platforms Features

• Agent Identity & Access Management: These platforms treat AI agents (bots, LLM-based “digital workers”, automation systems) as first-class identities. In practice this means creating, authenticating, provisioning and de-provisioning an agent identity with a lifecycle (on-boarding → runtime → off-boarding) just as you would a human account. They also register metadata such as agent origin, ownership, purpose, and lifetime. This approach addresses the fact that agents are often ephemeral, delegated, and context-bound rather than long-lived generic service accounts.
• Just-in-Time & Least-Privilege Access: Instead of granting standing, broad privileges to an agent, these platforms enforce access that’s scoped, temporary and tailored to the specific task or workflow. The model emphasises principles like zero standing privilege (ZSP) and just-in-time (JIT) authorization: the agent only gets the necessary access when needed, for the minimal duration. That helps mitigate risk from agents acting outside their intended bounds.
• Runtime Policy & Behavior Enforcement: Beyond simply granting access at provisioning time, AISPs embed a policy engine that monitors and controls agent behavior at runtime. That includes context-aware decisions (what the agent is doing, which tool it's invoking, what data it touches), dynamic revocation of privileges if the agent acts unexpectedly, and containment measures (sandboxing or rollback). This addresses the challenge that agents act continuously and autonomously rather than just log-in once.
• Data, Tool & Workflow Safeguards: Since agents may access sensitive data, coordinate with other agents, invoke external tools or make decisions across systems, AISPs provide controls to protect those workflows. That means governing what data agents can retrieve, transform or share, enforcing boundaries around external tool access, and guarding against specialized threats (for example prompt injection, agent-to-agent delegation abuse). This feature ensures that agents don’t become blind spots in data protection or system integrity.
• Governance, Auditability & Compliance: AISPs extend identity governance and compliance frameworks to agentic systems. They provide visibility into agent identities, mapping which agents exist, which workflows they run, what accesses they used, and the outcomes of their actions. They support audit logs, delegation tracing (which human or business process triggered the agent), and reporting to satisfy risk management, regulatory or internal control requirements.
• Human Oversight & Accountability: Recognizing the risks of autonomous agents acting without direct human supervision, AISPs incorporate features for human-in-the-loop or human-on-the-loop oversight. They link each agent’s activity back to a human sponsor or owning business process, ensure that assignments are approved and traceable, and enable review or intervention when necessary. This preserves accountability and supports risk controls even in a highly automated agentic environment.
• Hybrid & Distributed Agent Support: Many enterprises operate agents across cloud, on-premises, edge or disconnected environments. AISPs are designed with that reality in mind—they support agent identities that span distributed systems, hybrid landscapes, and even environments disconnected from the central cloud. They also adopt modern identity constructs (e.g., decentralized identifiers, verifiable credentials) to support mobility and interoperability of agent identities across systems.

Different Types of Agentic Identity and Security (AISP) Platforms

• Agent Identity & Access Management: This capability ensures that autonomous agents (software bots, AI agents, automated workflows) are treated as fully recognised identities, not just as generic service accounts. It covers the provisioning, authentication, credentialing, versioning and de-provisioning of agent identities, as well as associating metadata about their origin, purpose and ownership. Traditional human-IAM models fall short in this area because agents are often ephemeral, delegated, move across domains, and require fine-grained access rather than broad, static permissions.
• Runtime Policy Enforcement & Access Control: Given that agents act autonomously (making API calls, orchestrating tools, interacting with systems), it’s not enough to define access once and forget. This type of capability dynamically enforces policies based on context (e.g., time, location, risk level, intent), behaviour, agent-type and other attributes. It supports least-privilege access, just-in-time authorization, revocation mid-workflow, and ensures that every agent action is traceable and controlled at run time.
• Data & Knowledge Protection in Agentic Workflows: Agents often access, manipulate or generate data; they may use internal modelling, knowledge bases, external APIs, or chain tasks among themselves. The platform must ensure that agents don’t misuse or leak sensitive data, don’t gain excessive knowledge access, and that their workflows are constrained so they cannot escalate privileges or exfiltrate information. Protecting the “knowledge” and data layer in agentic contexts is therefore distinct from classic IAM.
• Operational Integrity & Resilience of Agentic Systems: This involves ensuring that the agentic systems behave safely, reliably and within defined bounds. It covers detection of anomalous agent behaviour (for example unexpected delegations, spawning sub-agents, colluding or chaining in unapproved ways), monitoring the lifecycle of agents, preventing identity or credential sprawl, and maintaining trust across agent-to-agent or agent-to-system communications. Agents can scale rapidly and their mis-behaviour can escalate fast, so this capability is critical.
• Governance, Risk & Compliance (GRC) for Agentic Identities: Because agents execute workflows autonomously, organisations must apply oversight: define ownership, accountability, review entitlements, audit logs, lifecycle management, policy controls, and compliance check-points for agents just as for human users. Many traditional IAM/GRC frameworks don’t cover dynamic, delegated, multi-agent workflows, so an AISP must extend governance to this new frontier.
• Visibility, Attribution & Human Oversight: To maintain trust and accountability, each agent action must be attributable: to the originating human or system, to the policy under which it operated, and the context in which it executed. Dashboards, logs, alerts and oversight mechanisms are needed so that humans can intervene when necessary, review agent behaviour, revoke agents, and ensure no “shadow agents” or unmanaged identities proliferate. Because agents act fast and sometimes invisibly, visibility is foundational.

Advantages of Agentic Identity and Security (AISP) Platforms

• Greater visibility and identity management for non-human agents: AISP enables organizations to discover, inventory, and manage identities that belong to autonomous agents or AI systems rather than just human users. Because agentic identities can be ephemeral, delegated, and context-bound, they require a different approach than traditional human accounts. By bringing these identities into view, firms can reduce shadow-agent risk and bring agent activities under governance.
• Dynamic and fine-grained access control tailored for agents: Because agents often act autonomously, execute workflows, or operate across systems, AISP supports access controls that adapt based on context, behaviour, and lifecycle rather than only static role assignments. That means permissions can be scoped tightly for agent tasks, reducing over-permission and minimizing blast radius if an agent is compromised.
• Strong governance, auditability, and lifecycle oversight of agentic workflows: With agentic systems acting with minimal human supervision, it becomes vital to have auditing, policy enforcement and lifecycle controls baked into the identity model. AISP platforms provide run-time policy enforcement and full lifecycle oversight of agent identities and behaviours. This helps organizations track which agent did what, when and why, thereby strengthening compliance, accountability and risk management.
• Unified identity/security framework across humans, machines and agents: Rather than maintaining separate silos for human identities, service accounts, machine identities and AI agent identities, AISP enables a unified approach so that all actor types are treated consistently under one identity and security regime. This simplifies management and policy application, and closes gaps where non-human identities might otherwise fall outside legacy governance.
• Support for ephemeral and rapidly changing agent lifecycles: Agents may spin up, execute tasks, then be torn down in seconds or minutes. AISP platforms are designed to manage ephemeral identities, context-bound credentials, delegation chains and automated revocation. This means an organization can safely scale autonomous agents without accumulating stale credentials or unmanaged identities.
• Alignment with modern architectures (zero-trust, multi-cloud, hybrid) and continuous control: Because agentic systems operate across cloud, hybrid, and dynamic environments, AISP architectures are often built to support continuous identity verification, policy enforcement in motion, and controls aligned with zero-trust principles. This ensures that agentic identities don’t become unmanaged perks of innovation, but are integrated into the same strategic security architecture as human and machine identities.
• Operational efficiency and safer automation through identity-first controls: By automating the identity, access and lifecycle controls of agents, organisations reduce manual overhead, minimise human error and enable faster safe innovation. Instead of manually provisioning and revoking agent credentials, AISP can embed such controls in the identity platform and scale safely. This improves agility and security together.
• Improved risk posture and mitigation of misuse by autonomous agents: Agents, by their nature of autonomous or semi-autonomous action, introduce novel risks—such as delegation abuse, anomalous behaviour, or privilege creep. AISP addresses these by embedding authentication, authorization, audit and behavioural telemetry of agentic identities—so that they can’t operate unchecked. This lowers the chance of rogue or misused agents causing data exposure or other harmful outcomes.

Types of Users That Use Agentic Identity and Security (AISP) Platforms

• Senior security leadership (e.g., CISOs and their teams): These are the executives and strategic decision-makers who oversee an organization’s overall security posture. With the rise of autonomous agents and systems acting on behalf of people or services, they turn to AISPs to extend their governance beyond traditional human identities. For example, AISPs help enforce policy, governance, auditability and least-privilege controls for these non-human actors: a capability that standard identity/access tools weren’t built for.
• Identity & Access Management (IAM) and directory teams: These teams traditionally manage user accounts, service accounts, roles and credentials. When agentic identities -- meaning identities for AI agents, bots or autonomous workflows -- enter the picture, the IAM teams are responsible for ensuring those identities are properly authenticated, authorized, audited and governed. Unlike static machine identities, agentic identities may be ephemeral, dynamically scoped and task-bound, increasing complexity.
• Cloud/Platform/DevOps engineers: These are the practitioners deploying infrastructure, services and automation pipelines where agentic identities frequently live and act. They use AISPs to embed runtime controls, ensure that agents accessing APIs or orchestration layers are properly managed, and avoid over-privileged or lingering agent credentials. Their interest is operational: ensuring that agents behave securely in cloud or hybrid environments.
• Compliance, risk & audit professionals: As agentic systems proliferate, governance and audit demands grow. These users need assurance that agentic identities are traceable, compliant with regulation, properly delegated, and that decisions or actions by agents can be attributed and audited. They rely on AISPs for logging, delegation chains, policy enforcement and evidence of control over autonomous digital actors.
• Business-unit or functional leaders deploying AI agents: These are the stakeholders who want to leverage autonomous agents for business value (in marketing, operations, HR, customer service etc.). They’re not traditionally in the security team but they need to ensure their agentic initiatives don’t create unmanaged risk. AISPs let them move faster while still having guardrails, ensuring that agentic workflows are within policy, scoped correctly and auditable.
• Security operations / incident response teams: These practitioners monitor, detect, and respond to threats. With agentic identities now part of the attack surface, they use AISPs to monitor agent behaviour, detect anomalous agent-driven access, respond to unauthorized workflows and incorporate agents into their SIEM/SOAR workflows. Agentic identities can act quickly and span many systems, making this especially important.
• AI/ML platform and data engineering teams: These teams build the infrastructure powering agentic systems – orchestration, pipelines, agent workflows, model deployments. They must embed identity, trust, access and logging into their systems so that agents operate with the right permissions, don’t create identity sprawl, and their behaviours are monitored. AISPs give them the mechanisms to embed these controls end-to-end in agentic workflows.
• Third-party vendors, service providers, system integrators: Many organisations rely on external parties to develop or operate agentic systems. Those external parties become users of the enterprise’s AISPs too – their agentic identities must be subject to the same governance, access control and auditing as internal ones. Without it, unmanaged agent identities from vendors can become a risk vector.
• Legal and ethics teams: As autonomous agents make decisions or take actions, legal and ethics stakeholders need transparency, accountability, governance and traceability. They rely on AISPs to demonstrate who authorized an agent, what it did, why it did it, and how it interacted with data and systems: essential for mitigating reputational or regulatory risk.
• End-users (indirectly impacted): While they are not direct administrators of AISPs, employees, customers or other users are impacted when agents act on their behalf or act with their data. The identity and security controls around those agents influence trust, privacy, experience and safety. Ensuring proper agentic identity governance benefits these end-users by reducing risk of misuse, error or uncontrolled automation.

How Much Do Agentic Identity and Security (AISP) Platforms Cost?

While there is limited public data on precise price tags for Agentic Identity and Security Platform (AISP) solutions, enterprises considering these platforms should expect significant investments. Because these platforms are still emerging, pricing is largely customized based on scope, scale, and infrastructure integration. Analysts note that the market for AISP is projected to grow from a few billion dollars into the tens of billions by 2031. The complexity of securing autonomous agents, machine identities and dynamic workflows means that cost elements include more than just license fees—they often include ongoing governance, runtime enforcement, identity-access management, data protection, and human-oversight modules.

Thus, budget planning for an AISP should factor in initial setup (integration with existing identity platforms, cloud/on-prem infrastructure, agent-onboarding), recurring operational costs (monitoring, analytics, policy maintenance, audits), and future scaling as more agentic systems are launched. Because many organizations are still piloting such platforms, vendors may offer tiered models (for example for smaller deployments) or usage-based fees tied to number of “agentic identities” or transactions, though these specifics are not broadly published. In short, while the market signals strong commitment and growth, cost estimates should be built from granular internal assessments rather than relying on standard fixed pricing.

What Software Can Integrate With Agentic Identity and Security (AISP) Platforms?

When we consider which types of software can integrate with an Agentic Identity and Security Platform (AISP): platforms designed to manage, monitor, and govern “agentic” identities (AI agents or agentic systems): it helps to think in terms of functional domains rather than separated silos.

First, identity and access management systems (IAM), including privileged access management (PAM) solutions, can integrate with an AISP because they already handle authentication, authorization, identity lifecycle and role/permission mapping for users or machines. When agents are added to the ecosystem, the IAM/PAM software becomes a bridge between “human/machine” identities and “agent” identities, allowing the AISP to leverage existing identity stores and access protocols (as described in the white-paper by the Cloud Security Alliance).

Next are governance, risk and compliance (GRC) platforms and audit/logging tools. These systems integrate with an AISP because the AISP must enforce policies, record agent behaviour, support traceability and accountability. The GRC or audit software consumes logs or events from agentic systems managed by the AISP, enabling oversight of decisions made by agents, compliance with regulatory frameworks, and risk management over non-human actors.

Third, data-access, knowledge management and data-protection platforms tie in closely. Agents often act on data or on behalf of users to access knowledge bases, APIs, storage systems. The AISP must integrate with software that manages data classification, data access control, and knowledge-flow governance so that when an agent requests data or acts upon a tool, that action is governed by the appropriate identity/access context. For instance, the “data and knowledge protection” pillar of AISP refers to this type of integration.

Fourth, software orchestration platforms, multi-agent management systems or agent orchestration frameworks also integrate with the AISP because they manage the workflows, tool invocation and inter‐agent communication. The AISP provides the security, identity and policy enforcement layer for those orchestration platforms: when an agent uses the orchestration engine to call a tool or another agent, the AISP ensures the identity and access context is valid, the agent is authorised, and the operation is logged and governed. For example, the launch of an “Agentic Identity Hub” by Descope shows how orchestration software can connect to an identity/authz layer for agents.

Fifth, infrastructure, cloud, hybrid or SaaS platform software integrate with AISP solutions because many agents deploy in those environments, access APIs, SaaS tools, cloud services. The AISP must be able to enforce identity and access policies across those environments. So cloud management platforms, service-accounts/secret-management systems and SaaS orchestration software all participate in the integration. The identity/agent flows cannot remain isolated in one environment when the agent uses multi-cloud, hybrid or SaaS resources.

Finally, monitoring, analytics, threat-detection and behavioral-risk software integrate with the AISP because the unusual behaviours of agents (autonomous, tool-invoking, orchestrating across systems) raise unique risks. Thus behavioral analytics platforms or identity-threat-detection systems need to receive agent-identity and activity data from the AISP in order to detect anomalies, misuse, unauthorized delegation or privilege-escalation by agents acting autonomously.

The types of software that integrate with an AISP cover the identity/authorization stack (IAM/PAM), governance/audit tools (GRC/logging), data/knowledge platforms (data management and protection), orchestration/agent management systems, infrastructure/cloud/SaaS platforms, and monitoring/analytics/risk-detection systems. The goal is that existing software domains plug into the AISP’s identity and policy engine so that agents can be managed just as securely and governably as human or machine identities.

What Are the Trends Relating to Agentic Identity and Security (AISP) Platforms?

• The elevation of AI agents to first-class identities: Platforms in the AISP category are increasingly treating autonomous AI agents (not just human users or conventional machine accounts) as identities that need their own lifecycle, privileges, and governance. Traditional IAM was built for human users or long-lived service accounts; these agentic systems create ephemeral identities, dynamic delegation, autonomous behaviour, and cross-domain execution.
• Shift toward runtime, context-aware enforcement rather than static access grants: In the agentic era, it’s not enough to grant permissions at “login” and forget about them. Agents may start tasks, delegate subtasks, move across systems, and act autonomously. Thus AISPs emphasise dynamic, context-aware access control, just-in-time provisioning, behavioural risk signals, and real-time monitoring of agent actions.
• Convergence of agent identity security with data, operations and governance domains: The security challenge isn’t only about managing agent identity; it’s also about how agents access data, interact with systems, and how their decision flows are governed. AISPs are beginning to merge identity, data security and operational governance into a unified framework.
• Emergence of specialized frameworks, standards and ecosystem building for agentic identity security: Because agentic AI introduces new security parameters (delegation chains, ephemeral identities, multi-agent systems, cross-agent communications), new frameworks and standards are being developed (for example from Cloud Security Alliance) to guide identity, access and delegation in these contexts.
• Growing urgency driven by proliferation of AI agents and increased risk surface: Agentic AI is no longer a theoretical exercise—enterprises are already deploying or piloting agents in many functions, which increases the number of identities, sessions, and interactions to secure. Meanwhile new attack surfaces emerge (e.g., agent impersonation, unauthorized delegation, prompt injection).
• Adoption of Zero Trust principles extended into agentic contexts: Many of the emerging AISP platforms and strategies emphasise the application of Zero Trust principles (verify every identity, grant least privilege, continuous monitoring, assume breach) specifically tailored to autonomous agents, their lifecycles and their access patterns.
• Hybrid, distributed and edge environments complicate identity and agent security: Many agents operate across cloud, on-premises, and edge environments. Traditional identity systems often assume centralised models. AISPs are shifting to support distributed identities, disconnected or intermittently connected cases, and bridging domains.
• Increased focus on traceability, accountability and auditability in agentic systems: As agents act autonomously and possibly delegate tasks to other agents, it becomes critical to maintain audit trails, delegation graphs, attribution (which human/system triggered the agent), and visibility into decisions and actions. AISPs are embedding features for traceability.
• Market opportunity and vendor innovation around AISP as a distinct category: Analysts such as Aragon Research are defining AISP as an emerging category and forecasting growth; vendors are starting to build solutions specifically targeted at agent identity & security rather than simply extending IAM.
• Interplay between governance, risk, and compliance (GRC) and agentic identity/security: With agentic systems acting across domains and possibly making decisions with business, regulatory or safety implications, governance frameworks must accommodate agent risks, their decision-flows, auditability, policy enforcement and risk assessment. AISPs integrate GRC capabilities tied to agents.

How To Select the Right Agentic Identity and Security (AISP) Platform

Selecting the right agentic identity and security platform (AISP) demands a clear understanding of both your organisation’s AI-agent landscape and the evolving threat surface that comes with autonomous digital workers. First, you should map out how many AI agents or agentic systems your enterprise intends to deploy, what kinds of tasks they will execute, where they will live (on-premises, in cloud, hybrid) and how they will interact with data, users, and other agents. This establishes your baseline for required identity, access, data, and governance controls.

Once you have that baseline, evaluate platforms by examining their support for identity and access management of agentic identities. Because autonomous agents are not like human users or traditional service accounts, the platform must allow you to define, authenticate, track and manage agent identities, their permissions, lifecycles and relationships. Research in this space identifies agent identity & access management as one of the “six pillars” of AISP capabilities.

Equally important is how the platform protects data and knowledge assets that agents will touch. Agents may generate, access, transform or share sensitive data, often at machine speed, so you want a vendor that can prevent misuse, enforce least-privilege access and guard against prompt injection or other misuse of agent workflows. One article outlines data & knowledge protection as a key capability.

You also need to assess the platform’s ability to enforce runtime policy dynamically—meaning it must do more than assign static roles and permissions. Since agents operate in unpredictable ways, the AISP should support dynamic authorization at runtime based on context, intent and behaviour, with auditing and traceability built in. Without such dynamic runtime controls you risk what’s called the “Access-Trust Gap” where agents can access more than they actually should.

Governance, risk and compliance (GRC) must be integral to the platform. You’ll want support for logging, attribution, oversight, audit trails, human-in-the-loop review, and agent accountability. These capabilities ensure you can demonstrate oversight of agentic identities in the same way you govern human identities. The research describes agentic GRC as another pillar.

When comparing vendors, focus on how well they integrate with your existing ecosystem: do they play nicely with your identity access management (IAM), privilege access management (PAM), data security tools and cloud or hybrid infrastructure. A platform that requires a rip-and-replace of your stack can slow adoption or create security gaps during transition. According to one guide, you should evaluate “deployment flexibility: SaaS, hybrid, or on-prem” as part of your decision.

Performance, scalability and innovation matter too: as your agentic workforce grows, the solution must scale to potentially thousands or even millions of agentic identities, and handle API-first, event-driven operations. One research note forecasts the AISP market rising dramatically, underscoring the scale dimension.

Finally, don’t neglect the human side: change management, operational processes and clear roles for oversight of agentic identities. Even the best tool will fail if you don’t define who reviews agent workflows, who authorizes agent lifecycles, how you respond when an agent behaves unexpectedly, and how you build accountability into your operating model.

In short, selecting the right AISP involves aligning your use-case and risk profile, ensuring the vendor supports agent identity, access, data protection, runtime policy enforcement, governance and ecosystem integration, and making sure your organisation is ready operationally to manage this new class of digital identities.

On this page you will find available tools to compare agentic identity and security (AISP) platforms prices, features, integrations and more for you to choose the best software.