AI regulation in 2026: what governance gaps teams are missing

TL;DR: AI regulation in 2026 is being shaped by overlapping laws, delayed deadlines, and continued movement in jurisdictions such as Korea and Vietnam, according to Holistic AI. The practical takeaway is that compliance teams cannot wait for one regime to settle before building governance, monitoring, and documentation controls.

NHIMG editorial — based on content published by Holistic AI: AI Regulation in 2026: Navigating an Uncertain Landscape

Questions worth separating out

Q: How should organisations govern AI systems under multiple regulatory regimes?

A: They should start with a single governance baseline for identity, access, logging, and approval evidence, then add local regulatory overlays for sector and jurisdiction requirements.

Q: Why do AI regulations create more risk for high-impact use cases?

A: High-impact use cases attract stricter obligations because failures affect employment, access to services, fairness, or public trust.

Q: How do teams know whether AI governance is actually working?

A: Look for evidence that every AI interaction can be traced end to end, from identity and intent to output and enforcement.

Practitioner guidance

• Build a jurisdiction-by-jurisdiction control map Catalogue every AI use case against the highest applicable requirements for assessments, oversight, documentation, and monitoring, then keep that mapping under version control as laws change.
• Separate legal timing from governance readiness Prepare the evidence set now, including impact assessments, approval records, monitoring plans, and exception handling, so a delayed deadline does not become a delayed control baseline.
• Tie AI access to identity controls Record which human users, service accounts, and AI agents can trigger model inputs, outputs, or downstream decisions, and review those permissions as part of governance evidence.

What's in the full article

Holistic AI's full blog covers the jurisdiction-by-jurisdiction policy detail this post intentionally leaves for the source:

• The specific 2026 regulatory developments across the US, EU, Korea, Vietnam, and other jurisdictions.
• The article's breakdown of how risk-based rules converge on assessments, oversight, documentation, and post-deployment monitoring.
• The policy team's use-case examples for HR technologies, dynamic pricing, and generative AI regulation.
• The eBook preview that maps pending legal changes to practical governance actions for legal and security teams.

👉 Read Holistic AI's analysis of AI regulation in 2026 →

AI regulation in 2026: what governance gaps teams are missing?

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