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10/06/2026 11:44 pm
TL;DR: Only 40% of organisations believe they are AI mature, but just 22% meet objective readiness standards, while 61% report unsanctioned AI tools and 74% remain worried about security risk, according to JumpCloud’s Q1 2026 IT Trends Report. The gap is not deployment speed but whether identity, access, and governance can scale with AI at all.
NHIMG editorial — based on content published by JumpCloud: Q1 2026 IT Trends Report, The Dual Disconnect: Why Your AI Maturity Now Fails to Scale
By the numbers:
- 40% of organizations believe they are AI mature, but only 22% possess the objective IT foundation required to scale safely.
- 61% of organizations report the use of unsanctioned AI tools, creating significant visibility and governance gaps.
- 74% remain concerned about security risks, specifically unauthorized data access and AI-generated phishing.
Questions worth separating out
Q: How should security teams govern AI adoption when maturity scores look better than reality?
A: Security teams should anchor AI governance in identity and access controls, not self-assessed maturity.
Q: Why do shadow AI tools create an IAM problem instead of just an application risk?
A: Shadow AI creates an IAM problem because every unsanctioned tool introduces a new identity path, credential exposure point, or data connection that bypasses standard governance.
Q: What breaks when AI access is governed separately from human and NHI access?
A: Separate governance creates inconsistent policy enforcement, slower revocation, and blind spots in review.
Practitioner guidance
- Measure AI readiness against identity control coverage Map where AI-connected access is authenticated, authorised, logged, and reviewed.
- Inventory shadow AI as an access problem Track unsanctioned AI tools, browser-based AI use, and service connections that can reach company data.
- Unify human and non-human governance workflows Bring user access reviews, service account oversight, and AI-linked permissions into one governance model so policy, recertification, and revocation follow the same operating standard.
What's in the full report
JumpCloud's full report covers the operational detail this post intentionally leaves for the source:
- Survey methodology and respondent breakdown behind the AI maturity and readiness findings
- Budget and investment trend data that helps translate AI governance into planning decisions
- Additional findings on productivity, security concern, and infrastructure unification
- The report's broader discussion of how IT leaders are thinking about AI scale and control
👉 Read JumpCloud's Q1 2026 IT Trends Report on AI maturity and readiness →
AI maturity illusion and shadow AI: what IAM teams should do?
Explore further
12/06/2026 6:04 am
AI maturity is an access-governance claim, not a deployment claim. JumpCloud’s data shows that organisations are treating AI adoption as proof of readiness even when only 22% meet objective standards. That gap matters because identity control, not model enthusiasm, determines whether AI can be introduced safely into production workflows. Practitioners should read AI maturity as a control-state question, not a roadmap milestone.
A few things that frame the scale:
- 59.8% of organisations see value in a solution that simplifies non-human access management and introduces dynamic ephemeral credentials, according to The 2024 Non-Human Identity Security Report.
- 88.5% of organisations acknowledge that their non-human IAM practices lag behind or are merely on par with their human identity and access management efforts.
A question worth separating out:
Q: How do organisations know whether AI readiness is actually improving?
A: Improvement shows up when the organisation can reduce unsanctioned tool use, increase identity coverage for AI-linked access, and prove that permissions are reviewed and revoked on schedule. Readiness is measurable when identity controls can keep pace with how fast AI is adopted.
👉 Read our full editorial: AI maturity is outpacing identity readiness in enterprise IT
