Skip to main content
Shadow AI Audit

You think your firm runs three AI tools. The real number is closer to thirty.

Every regulated mid-market firm we audit has Shadow AI: personal ChatGPT accounts, browser extensions, embedded features in SaaS the firm already pays for, and contractor-built workflows nobody owns. Most clock between 15 and 50 tools the leadership team did not know existed. The Shadow AI Audit produces the inventory, classifies the data exposure, and installs the governance line.

What the Audit finds

Four classes of Shadow AI every engagement uncovers.

The Audit produces a structured inventory. It is not a long list of unrelated tools; it is four predictable classes, each with its own governance fix. Every Audit names where the firm sits on each class.

The output the same week as the readout: a one-document inventory, a kill/fix/keep verdict per tool, a sequenced remediation plan, and a governance line the firm can stand behind.

Class
01

Personal accounts on the firm’s data

Free-tier ChatGPT, Claude, Gemini, Perplexity, and browser-side AI extensions used by staff against confidential firm material. Logged in the personal account, not the firm. Found via expense-report keyword search and structured employee survey.

Class
02

Embedded AI inside paid SaaS

Microsoft 365 Copilot, iManage AI, Salesforce Einstein, HubSpot AI, Zoom AI, Otter, Fireflies. Enabled by default in the SaaS contract the firm already pays for. The data-handling clause for the AI feature is rarely the same as the base SaaS contract.

Class
03

Contractor-built and orphaned workflows

Custom integrations that call an external LLM API: form-handler workflows, customer-support automations, document-classification jobs. Developer left the firm; the workflow is still running on the same API key. The vendor has a contract with someone who no longer works at the firm.

Class
04

Browser extensions and consumer apps

Grammarly, Wispr, Cluely, Notion AI, Microsoft Edge’s built-in copilot, Arc’s Max features, Pocket AI summaries. Each touches firm content. None are in the IT inventory. Detected via DNS-level traffic analysis and endpoint browser-extension survey.

What HIP delivers

A complete picture the firm can act on inside two to six weeks.

01

Full Shadow AI inventory

Every tool, account, embedded feature, and contractor-built workflow detected via expense, survey, endpoint, and traffic signals. Classified by data-class touch and ownership.

02

Keep, fix, or kill verdict per tool

For each tool, a written verdict against the firm’s governance line and regulatory perimeter. Reasoning documented so the decision survives the next leadership rotation.

03

Remediation roadmap with named owners

A sequenced plan: which tools to kill this week, which to fix with enterprise licensing or DPA, which to replace with sanctioned alternatives, and which to keep. Each step has a named owner and a turnaround commitment.

04

Governance line the firm can defend

A one-document governance posture: approved tools per data class, sub-processor list, vendor DPAs, the approval path for new tools, and the named owner of the line. Built to be shared with a regulator, LP, client, or auditor on request.

Fit criteria

Firms where Shadow AI Audit fits cleanly, and where it does not.

Strong fit

  • Regulated, fiduciary, or privileged-work firm with 50 to 500 employees and AI already in production.
  • Leadership cannot produce a written inventory of every AI tool in the firm this week.
  • A regulator, LP, auditor, or client has begun asking AI questions, or is expected to.
  • Leadership wants to govern Shadow AI, not just ban it.

Not a fit

  • Firms running zero AI today; there is no shadow to audit.
  • Firms whose plan is to block all AI at the firewall and call it solved. Blocking moves Shadow AI to personal devices and personal hotspots. The exposure stays; visibility drops to zero.
  • Firms looking for a one-off compliance certificate. The Audit is a working diagnostic, not a stamp.
Common questions

What leadership asks before the Shadow AI Audit.

How do you find tools nobody at the firm knows about?

Five parallel channels: expense-report keyword search across 12 months (ChatGPT, Claude, OpenAI, Anthropic, Perplexity, Copilot), structured anonymous employee survey, endpoint browser-extension inventory, SaaS contract walkthrough for embedded AI features, and DNS-level traffic sample. The five together typically find 15 to 50 tools where leadership estimated five.

Will staff cooperate with the survey?

The survey is positioned as discovery, not enforcement. The promise is that current tools are not punished; only future ones outside the governance line are. Cooperation rates are high when leadership communicates the change directly and the Audit moves quickly. Where cooperation is low, the other four channels still produce a defensible inventory.

What is the difference between this and a regular AI audit?

The AI Operating Audit covers governance, throughput, and tool inventory across the firm. The Shadow AI Audit is the same engagement scoped specifically toward unsanctioned use: it weights detection and inventory heavier and remediation slightly lighter. Most firms find that what starts as a Shadow AI Audit becomes a full AI Operating Audit by week three because the inventory is the entry point to the rest of the work.

How long does the Audit take and what does it cost?

Two to six weeks depending on firm size and entity count. Standard single-entity Shadow AI Audit is from $15,000. Most firms continue into the Fractional CAIO retainer afterward, quoted in the Audit readout.

More sectors

Other regulated sectors where HIP fits.

Start

The Audit pays for itself either way. Apply to work with HIP.

Every engagement begins with a short fit review and the Shadow AI Audit. Most firms continue into the AI Operating Partner relationship from there. If there is not strong mutual fit, we tell you directly.