---
id: "question-auditing-black-box-ai"
type: "open-question"
source_timestamps: ["§ 2. Conventional Tools Don't Translate"]
tags: ["cloud-security", "vendor-management", "auditing"]
related: ["action-demand-ai-transparency", "claim-conventional-tools-fail"]
resolution_path: "Development of standardized, third-party auditing frameworks specifically for cloud-hosted AI infrastructure, or regulatory mandates for transparency from hyperscalers."
source_title: "Research: Conventional Cybersecurity Won't Protect Your AI"
source_url: "https://hbr.org/2026/01/ts-research-conventional-cybersecurity-wont-protect-your-ai"
sources: ["tail2"]
sourceVaultSlug: "hbr-seg-tail2"
originDay: 2
articleStem: "hbr-tail-128-cybersecurity-wont-protect-ai"
sourceUrl: "https://hbr.org/2026/01/ts-research-conventional-cybersecurity-wont-protect-your-ai"
sourceTitle: "Research: Conventional Cybersecurity Won’t Protect Your AI"
---
# How can enterprises effectively audit proprietary 'black box' AI services?

**Open question.** A cybersecurity company was locked into a major cloud provider's proprietary AI service, unable to audit the underlying safeguards (see [[claim-conventional-tools-fail]]). The author advises 'demanding transparency' ([[action-demand-ai-transparency]]), but the exact **technical or contractual mechanisms** to achieve auditability — in a market dominated by a few massive cloud vendors — remain unresolved.

**Possible resolution path:** Standardized, third-party auditing frameworks specifically for cloud-hosted AI infrastructure, or regulatory mandates for transparency from hyperscalers.

**Enrichment.** External analyses reinforce the difficulty of auditing proprietary Copilot-class internals and point instead toward perimeter mitigations (DLP tags, labeled emails, tenant restrictions) — a pragmatic stopgap that underscores, rather than solves, the transparency gap. Governance regimes like the EU AI Act are the likeliest lever for mandated auditability of high-risk AI.