Notifications
Clear all
Topic starter
15/08/2026 6:13 pm
TL;DR: AI security posture management now extends beyond model and data monitoring to identity-first governance, because Obsidian Security argues that AI workflows create new access paths, compliance obligations, and cross-functional control gaps across the lifecycle. The practical implication is that AISPM only works when teams can continuously inventory AI assets, govern privileges, and prove accountability at scale.
NHIMG editorial — based on content published by Obsidian Security: The AISPM Market Guide: Navigating AI Security Posture Management
Questions worth separating out
Q: How should security teams govern sensitive data used by AI systems?
A: Security teams should treat AI as a data consumer that needs policy boundaries, not just authentication.
Q: Why does AI adoption create an identity governance problem?
A: AI adoption creates an identity governance problem because the system that accesses data is often only loosely visible to IAM.
Q: What do organisations get wrong about AI security coverage?
A: They often treat AI as a single category and then count tool coverage as governance.
Practitioner guidance
- Inventory every AI asset and connector Create and maintain a live inventory of AI models, copilots, agents, SaaS integrations, and data sources.
- Map AI workflows to delegated access Document which service accounts, OAuth grants, API keys, and workspace permissions each AI workflow inherits.
- Enforce policy-as-code for AI controls Translate AI governance requirements into machine-enforceable policies for approval, logging, data access, and retention.
What's in the full article
Obsidian Security's full blog post covers the operational detail this post intentionally leaves for the source:
- The AISPM maturity stages and the control activities associated with each stage
- The article's regulatory mapping across the EU AI Act, GDPR, ISO 42001, and NIST AI RMF
- Examples of how AI posture controls are organised across security, compliance, and MLOps teams
- Obsidian Security's platform-oriented view of AI visibility, alerting, and automated remediation
👉 Read Obsidian Security's AISPM market guide and governance framework →
AISPM and identity-first governance: are your controls keeping up?
Explore further
15/08/2026 6:19 pm
AI security posture management is becoming identity governance for machine-driven workflows. The article is strongest when it frames AISPM as continuous control across AI assets, not just model monitoring. Once AI systems can call tools, access SaaS data, and inherit permissions, the governing question becomes who or what is authorised to act, for how long, and with what audit trail. That is classic identity governance territory, just applied to AI workflows. Practitioners should stop treating AISPM as a separate niche and fold it into IAM, PAM, and workload identity governance.
A question worth separating out:
Q: Who is accountable when an AI system makes a harmful decision?
A: Accountability should follow the identity chain that authorized, configured, or triggered the action, including the human owner, the platform team, and any delegated agent or tool account. If the organisation cannot name that chain, the governance model is too weak for regulated AI use.
👉 Read our full editorial: AI security posture management now hinges on identity-first controls
