Why do organizations need AiSPM?

Organizations need AiSPM when AI adoption creates security and visibility gaps across models, applications, agents, data, tools and integrations. AiSPM helps security leaders understand what exists, identify risk, prioritize remediation and monitor how the posture changes over time.

What is the difference between AI security and AiSPM?

AI security is the broader discipline of protecting AI systems and the data, identities, models and infrastructure around them. AiSPM is a posture-management approach that focuses on discovering the AI environment, assessing its security posture, prioritizing risks and continuously improving controls.

What does an AI security risk assessment include?

An AI security risk assessment can examine AI inventory, architecture, data flows, identities and access, model security, agent behavior, integrations, prompt injection exposure, supply-chain dependencies, governance controls and evidence. The exact scope should be defined around the organization's AI use cases.

What is AI agent security?

AI agent security focuses on protecting AI agents and agentic workflows from risks involving identity, permissions, delegation, tool access, instructions, data, execution and downstream actions. AiSPM can bring these risks into a broader enterprise posture-management view.

How does AiSPM support AI governance?

AiSPM can connect technical AI inventory and security findings with governance requirements, ownership, accountability and evidence. This helps organizations move from policy-only governance toward measurable operational controls.

What AI security risks should enterprises monitor?

Relevant risks include prompt injection, AI agent security risks, model security risks, data exposure, identity and access risks, third-party and AI supply-chain dependencies, insecure integrations, shadow AI and gaps in governance or compliance.

How is AiSPM different from CSPM?

Cloud Security Posture Management focuses on cloud infrastructure and cloud configuration posture. AiSPM focuses on AI-specific assets, workflows, models, agents, data, integrations and AI security risks. The two approaches can complement each other in enterprise environments.

When should an organization start an AiSPM program?

An organization should consider AiSPM when AI moves beyond isolated experimentation into production applications, customer-facing services, business workflows or autonomous/agentic processes. Early posture management can help establish visibility and controls before AI risk becomes harder to manage.

How does Indrasol help with AiSPM?

Indrasol can help organizations assess their AI security posture, establish AI inventory and risk visibility, align AI security with governance and compliance, prioritize remediation and build an ongoing posture-improvement approach. The exact engagement scope should be tailored to the organization's AI environment.

AI Security Posture Management.For Enterprise AI.

See your AI security posture before AI risk becomes a business problem.

Indrasol helps organizations discover AI systems, understand AI security risks, assess governance and compliance exposure, prioritize what matters, and build a measurable AI security posture management program.

Discover AI applications, models, agents, data flows, APIs and integrations across your environment.
Assess AI security, governance, compliance and risk across the AI lifecycle.
Prioritize the risks that could affect security, data, customers, operations and enterprise growth.

Security-focused assessment. Practical recommendations. Clear next steps.

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Related practices

Can You See Your Enterprise AI Security Posture?

AI adoption can introduce new models, AI applications, agents, APIs, data sources, identities and third-party services faster than traditional security processes can track them. The result is a growing gap between what the organization believes it has deployed and what is actually operating.

Enterprise AI Security Blind Spots

Unknown AI systems and shadow AI applications can create inventory and ownership gaps.

AI agents can introduce new identity, access, delegation and execution risks.

Prompt injection and tool manipulation can change how AI systems behave.

Sensitive data can move through models, applications, APIs and integrations without sufficient visibility.

AI model security and AI supply chain dependencies can create risks outside traditional application security controls.

AI governance and AI compliance requirements can become difficult to demonstrate without evidence across the AI lifecycle.

Not sure where AI is running in your enterprise? Start with a posture discovery conversation.

What Is AI Security Posture Management (AiSPM)?

AI Security Posture Management (AiSPM, also written AI-SPM or AISPM) is an approach to continuously discover, understand, assess, prioritize and improve the security posture of an organization's AI environment.

It brings visibility across AI applications, models, agents, identities, data, APIs, integrations and related controls so security and technology leaders can manage AI risk based on business impact. The goal is not to replace existing security or governance programs, AiSPM complements them with AI-specific visibility and risk context.

What AiSPM helps discover

AI applications and services
Models and model providers
AI agents and agentic workflows
AI APIs and exposed endpoints
Data sources and retrieval systems
Identities, service accounts, API keys, and delegated permissions
Plugins, tools, MCP servers, and enterprise integrations
Third-party AI services and supply-chain dependencies
Shadow AI and previously unknown AI usage

What AiSPM helps evaluate

Configuration and exposure
Identity and access risk
Sensitive data access and movement
Third-party and supply-chain dependencies
AI-specific vulnerabilities and attack paths
Policy and governance alignment
Runtime behavior and unexpected actions
Risk changes over time

Why Do Enterprises Need AiSPM?

Enterprise AI expands the attack surface because AI systems increasingly connect models and automation to data, identities, applications, APIs, and business processes. Traditional security tools remain important, but they may not provide enough AI-specific context.

Shadow AISensitive data leakageExposed AI APIsExcessive AI permissionsAI misconfigurationsAI supply-chain riskVulnerable third-party or open-source modelsExcessive AI agent autonomyInadequate AI monitoringLack of continuous AI governancePrompt injection and context manipulationModel and data poisoningModel extraction and theftIdentity and delegation risk

From AI Adoption to Secure AI Adoption

AI adoptionKnow what is being deployed
AI visibilityUnderstand assets, identities, data, and integrations
Risk contextConnect technical findings to business impact
Continuous postureDetect changes as the AI environment evolves
Secure scaleRemediate priority exposures without slowing responsible innovation

A Practical AI Security Posture Management Lifecycle

Indrasol's AiSPM approach is designed around a practical lifecycle rather than a one-time checklist.

Discover

Build visibility into AI applications, models, agents, data, APIs, identities and integrations.

Outcome: A practical inventory of the AI environment.

Understand

Map ownership, architecture, access, dependencies, data flows and business context.

Outcome: Turn inventory into usable security context.

Assess

Evaluate AI security risks, governance gaps, compliance exposure and control maturity.

Outcome: A clear view of posture strengths and gaps.

Prioritize

Rank risks based on likelihood, exposure, business impact and remediation urgency.

Outcome: Focus teams on the risks that matter most.

Protect & Implement

Define and implement practical controls, guardrails and remediation actions.

Outcome: Reduce avoidable exposure while supporting AI adoption.

Monitor & Improve

Track changes, reassess risk and continuously improve the organization's AI security posture.

Outcome: A repeatable AI security improvement cycle.

What Our AiSPM Approach Covers

Practical coverage across discovery, assessment, governance, agents, models and continuous improvement.

AI Discovery & Inventory

Identify AI applications, models, agents, APIs, data sources, integrations and ownership to create a practical AI inventory.

AI Security Risk Assessment

Assess AI security risks across applications, models, agents, data, access, integrations and operational controls.

AI Governance & Compliance

Connect AI governance requirements with security controls, accountability and evidence so organizations can manage AI compliance more effectively.

AI Agent & Agentic AI Security

Evaluate AI agents and agentic workflows for identity, delegation, tool access, execution and control risks.

AI Model Security

Assess model-related security risks, dependencies and protections across the AI lifecycle.

AI Supply Chain Security

Identify third-party models, components, services and dependencies that can introduce AI supply-chain risk.

AI Risk Prioritization

Translate technical findings into prioritized actions based on exposure, business impact and control gaps.

Continuous Posture Improvement

Establish monitoring, reassessment and improvement practices as AI systems, configurations and business use cases change.

How an AiSPM engagement typically progresses

Step 1: Scope & Discovery Kickoff

Align on AI use cases, environments, stakeholders, and the visibility sources available for discovery.

Expected outcome: A shared starting point for the AiSPM engagement.

Step 2: AI Asset & Context Mapping

Inventory AI applications, models, agents, APIs, data paths, identities, and integrations.

Expected outcome: A clearer picture of what AI exists and how it connects.

Step 3: Risk Assessment & Prioritization

Evaluate exposures using business criticality, data sensitivity, permissions, and attack-path context.

Expected outcome: A ranked set of AI security priorities.

Step 4: Control Recommendations

Define practical controls for access, configuration, data protection, integrations, and governance.

Expected outcome: An actionable remediation and control roadmap.

Step 5: Remediation Support

Help teams close high-priority findings and assign clear ownership for follow-through.

Expected outcome: Reduced exposure with clear accountability.

Step 6: Monitor & Improve

Continuously monitor posture changes and measure risk reduction, recurring findings, and control effectiveness.

Expected outcome: A repeatable AI security program that keeps pace with AI adoption.

AiSPM vs Traditional Security & Governance Approaches

AiSPM should not be treated as a replacement for established security and governance technologies. Its value is in adding AI-specific asset visibility, context, and continuous posture management.

Solution	Primary focus	What it sees	AI context	Continuous AI posture
AiSPM	AI security posture	AI assets, identities, data, integrations, configurations, dependencies	High	Yes
CSPM	Cloud configuration	Cloud resources and configurations	Limited unless integrated	Yes
CNAPP	Cloud application protection	Cloud, workloads, applications, vulnerabilities	Varies by platform	Yes
Vulnerability Management	Vulnerabilities	Known vulnerabilities and assets	Usually limited	Yes
IAM	Identity and access	Users, roles, permissions, credentials	AI identity context varies	Yes
DLP	Data protection	Sensitive data movement and policy violations	AI context varies	Yes
AI Governance	Policies and responsible use	Policies, controls, risk processes, evidence	High	Often periodic
AI Runtime Security	Runtime behavior	AI interactions, requests, actions, runtime events	High	Yes
Traditional GRC	Enterprise risk and compliance	Controls, policies, evidence, risk registers	AI context varies	Often periodic

Move From AI Visibility Gaps to Measurable Risk Reduction

A continuously maintained view of AI assets and ownership

Risk identified and prioritized proactively

Security, governance and compliance aligned

Risk mapped across AI components and dependencies

Defined evidence and accountability for key controls

Risk-based prioritization guides remediation

AiSPM for Organizations Scaling AI

SaaS and B2B software

Protect AI-enabled products and enterprise customer environments.

AI startups

Establish security and governance foundations while moving from experimentation to production.

FinTech

Manage AI security, data exposure and governance requirements around sensitive financial workflows.

HealthTech

Improve visibility and control around AI systems handling sensitive information.

Cloud and managed service providers

Establish repeatable AI security practices across environments.

Defense and government contractors

Strengthen AI security posture and evidence-driven risk management.

Manufacturing and enterprise technology

Manage AI models, agents, data and connected systems across operational environments.

Turn AI Security From a Blind Spot Into a Managed Posture

Indrasol combines cybersecurity, cloud, AI, data and governance capabilities to help enterprises address AI security as an operational and business-risk discipline, not as a standalone policy exercise.

Security-first approach to AI adoption
Practical AI security posture assessment
Alignment of AI security, AI governance and AI compliance
Risk prioritization based on exposure and business context
Support across assessment, implementation, monitoring and improvement
Enterprise-oriented approach spanning technology, security and governance stakeholders

Are you ready to measure your AI security posture?

Frequently Asked Questions About AiSPM

Direct answers to the questions security and technology leaders ask when scoping an AiSPM programme.

AI Security Posture Management is an approach to continuously discover, assess, prioritize and improve the security posture of an organization's AI environment. It provides visibility across AI applications, models, agents, data, identities, APIs, integrations and related controls.

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Are You Ready to Measure Your AI Security Posture?

AI adoption is expanding the enterprise attack surface. Get a clear view of your AI environment, understand the risks that matter, and define the next actions for a stronger AI security posture.

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