Shadow AI and non-human workforce governance at Gartner SRM 2026

At a glance

What this is: SailPoint’s Gartner SRM 2026 session agenda centers on shadow AI, agentic workforce governance, and identity-aware SOC operations.

Why it matters: For IAM and NHI teams, it underscores that autonomous agents and service accounts need continuous governance, not one-time onboarding.

👉 Register for SailPoint's Gartner SRM 2026 sessions on shadow AI and identity

Context

Shadow AI creates a governance gap when AI tools and autonomous agents begin acting with execution authority but do not appear in the normal identity inventory. In NHI terms, the issue is not just access sprawl, but unmanaged execution paths that inherit privileges, secrets, and data access outside established approval flows. This is the kind of control problem IAM teams were not built to absorb overnight.

SailPoint’s June 1 to June 3 presence at Gartner Security & Risk Management Summit frames the topic as an operational challenge for both NHI governance and SOC effectiveness. The vendor’s stated focus on visibility, control, and identity context reflects a broader pattern: practitioners are being asked to govern machine activity with human-era access models, which is typically a mismatch from the start.

Key questions

Q: How should security teams govern shadow AI before it spreads across the enterprise?

A: Start by discovering every AI tool, agent, and workflow that can act with execution authority, then map the NHI credentials behind it. Assign ownership, scope access to the smallest viable task, and enforce review and offboarding so unmanaged systems do not become permanent blind spots.

Q: Why do AI agents create more risk than traditional automation jobs?

A: AI agents can change actions, tool use, and data access dynamically, which makes their privilege profile less predictable than a fixed script or batch job. That variability increases the need for continuous entitlement review, short-lived credentials, and strong ownership.

Q: What is the difference between standard IAM review and NHI governance for agents?

A: Standard IAM review usually checks whether a subject has access, while NHI governance also tracks lifecycle, purpose, credential exposure, and runtime behaviour. For agents, that extra context matters because the risk is not only access, but how the identity is used after deployment.

Q: How can SOC teams use identity context to improve response to agent activity?

A: SOC teams should correlate alerts with the identity’s owner, intended purpose, and assigned privileges before escalating. That lets analysts distinguish expected automation from misuse, spot privilege abuse faster, and reduce alert fatigue caused by machine-driven activity that lacks context.

Background and context

Shadow AI and agentic workforce visibility

Shadow AI usually emerges when teams adopt AI tools, copilots, or agent workflows without central registration, ownership, or policy enforcement. In practice, that means the security team may know a tool exists, but not which accounts it can use, what data it can touch, or which downstream services it can call. For NHI governance, the challenge is that these systems often rely on service accounts, API keys, or delegated tokens that blend into legitimate automation. Once those identities are outside inventory and review, access becomes durable even when the tool itself is unofficial.

Practical implication: Inventory AI agents and the NHI credentials they use before you try to control their behaviour.

Identity context in the SOC

Identity context means bringing user, workload, and NHI entitlement data into detection and response so analysts can see who or what initiated an action, what privilege was used, and whether the access path was expected. For agents and service accounts, this matters because conventional alerting often records the event but not the authority behind it. Without identity context, the SOC is forced to investigate symptoms instead of privilege misuse. The result is slower triage, more false positives, and weaker escalation decisions.

Practical implication: Correlate agent and service-account activity with entitlement and ownership data inside your response workflows.

Non-human workforce governance and least privilege

A non-human workforce is not a metaphor. It is the growing set of bots, agents, workloads, and service identities that can execute tasks independently. These identities need lifecycle controls, scoped permissions, rotation discipline, and review cadences that reflect how quickly their purpose changes. Zero standing privilege and just-in-time access are relevant here because persistent access creates unnecessary blast radius when an agent is compromised or misused. Governance fails when machine identities are treated as static infrastructure rather than managed actors.

Practical implication: Apply the same lifecycle discipline to AI agents and service identities that you expect for high-risk human access.

NHI Mgmt Group analysis

Shadow AI is an NHI governance problem before it is an AI policy problem. Once an unsanctioned agent can call tools, read data, or trigger workflows, it behaves like a non-human identity with reach across systems. That means discovery, ownership, and privilege scoping must come first, or policy discussions remain theoretical. Practitioners should treat any unmanaged agent as a live identity risk.

Identity context belongs in the SOC because execution authority now travels with machines. When service accounts and agents operate at machine speed, response teams need to know which identity acted, what it was allowed to do, and whether the action matched its normal purpose. This sharpens alert triage and reduces the chance that automated misuse is mistaken for routine activity. The practical conclusion is clear: detection without identity context leaves a blind spot.

Non-human workforce growth is widening the blast radius of stale credentials and delegated access. The more autonomous systems rely on persistent tokens, shared secrets, and broad delegation, the more a single compromise can cascade. That makes lifecycle controls, segmentation, and time-bounded access more important than adding another approval layer. The field needs to move from static entitlement review to continuous NHI governance.

Identity-aware automation changes the control model for agentic AI. Traditional IAM assumes a mostly stable subject and a finite set of request paths. Agents break that assumption because they can change tasks, tool use, and access patterns dynamically. The named concept here is the runtime governance gap, which is the distance between what an agent can do at execution time and what the identity program can currently observe or constrain. Practitioners should close that gap with policy, telemetry, and ownership.

The security market is shifting from point controls to governance overlays for machine identity. Sessions like this signal that buyers are no longer asking whether AI agents need controls, but where those controls should sit across IAM, PAM, SOC, and data access. That shift will pressure teams to re-evaluate fragmented tooling and decide whether they can govern machines as first-class identities. Practitioners should plan for a control plane, not a one-off feature.

From our research:

• 98% of companies plan to deploy even more AI agents within the next 12 months, despite documented rogue behaviour in 80% of current deployments, according to AI Agents: The New Attack Surface report.
• Only 52% of companies can track and audit the data their AI agents access, leaving 48% with a complete blind spot for compliance and breach investigation.
• Use the OWASP Agentic AI Top 10 to translate those blind spots into concrete control priorities for agent identity and tool use.

What this signals

Runtime governance gap: the more AI agents inherit privileges from service accounts and tokens, the more security teams need continuous visibility instead of periodic certification. The governance model has to follow the execution path, not just the approval path, or machine identities will keep expanding beyond what the control set can see. That is why agentic AI should be treated as an identity program problem first. For a practical control lens, align the work with the NIST AI Risk Management Framework.

The operational signal for readers is straightforward: inventory quality now determines how quickly you can contain agent misuse later. If your organisation cannot prove who owns each agent and which data it can reach, the SOC will inherit uncertainty during every investigation. The right response is to tie discovery, review, and revocation into the same operating rhythm used for other high-risk NHIs.

For practitioners

• Map AI tools to accountable owners Create an inventory of sanctioned and unsanctioned AI tools, then assign owners for the service accounts, API keys, and tokens they use. If no owner exists, treat the identity as ungoverned until it is brought under review.
• Add identity context to SOC triage Feed entitlement, ownership, and purpose data into detection workflows so analysts can see whether an agent or service account acted within scope. This reduces time wasted on events that look suspicious only because the identity is unknown.
• Apply time-bound access to autonomous systems Use just-in-time approval and short-lived credentials for high-risk agent actions instead of persistent tokens. Pair that with periodic rotation and revocation checks so abandoned access does not linger after the workflow changes.
• Review broad delegated permissions Identify service accounts and agents that can reach multiple tools or datasets, then narrow their scope to the smallest viable task set. Broad delegation is a common path to excess blast radius when machine identities are reused across workflows.
• Tie AI governance to the NHI lifecycle Place discovery, onboarding, rotation, review, and offboarding under one lifecycle process so machine identities are not managed as exceptions. Use the NHI Lifecycle Management Guide to align those steps with your existing identity programme.

Key takeaways

• Shadow AI becomes an NHI issue as soon as autonomous tools gain execution authority and credentials.
• Agent growth is outpacing current governance because many organisations still lack full visibility into what their AI systems can access.
• Teams should combine discovery, ownership, scoped access, and lifecycle controls before agentic workflows become hard to unwind.

Key terms

• Shadow AI: Unapproved or unmanaged AI tools and agents that operate inside an environment without central visibility. In NHI terms, these systems often rely on hidden service accounts, tokens, or delegated access, which makes them hard to review, revoke, or monitor once deployed.
• Non-human workforce: The set of bots, agents, workloads, and service identities that execute tasks on behalf of the enterprise. These identities can create real business value, but they also need ownership, lifecycle controls, and least-privilege scoping because they act with execution authority.
• Identity context: The entitlement, ownership, and purpose information that explains why an action occurred and whether it was expected. For security operations, identity context turns raw alerts into decisions by showing which human or non-human identity acted and what it was allowed to do.
• Runtime governance gap: The distance between what an AI agent can do while running and what the identity programme can currently observe or constrain. This gap appears when access is granted upfront but behaviour changes later, making continuous monitoring and policy enforcement necessary.

What to expect at the briefing

SailPoint's full event listing covers the session-level detail this post intentionally leaves at the governance layer:

• June 1 and June 2 session timing, locations, and speaker details for teams planning attendance.
• The networking reception schedule for practitioners who want to connect with peers during the summit.
• The vendor's own session descriptions for identity-centric SOC strategy and shadow AI governance.
• Registration prompts and event logistics for those coordinating travel or internal attendance approvals.

👉 SailPoint's event page includes the session schedule, speaker details, and reception logistics for National Harbor.

Deepen your knowledge

Shadow AI discovery, agent ownership, and lifecycle controls are core topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building governance for autonomous systems and service identities, it is a strong fit.