Shadow AI governance: replace unapproved tools with safer workflows

Pax8 has published guidance on the risks of unapproved workplace AI and the role managed service providers can play in addressing them. For Australian employers, the practical task is to establish shadow AI governance without removing useful tools and leaving staff with no workable alternative.

The Pax8 discussion of workplace AI governance provides the starting point for this article, rather than a regulatory announcement. The process below turns that concern into specific checks for business owners, operations managers, finance teams and IT leaders.

Start shadow AI governance with the work, not the software

Shadow AI is AI used for business purposes without the organisation's approval or oversight. It can include a personal chatbot account, a meeting transcription service, a browser extension or an AI feature newly enabled inside existing software.

The problem is not simply whether a tool is popular or reputable. It is whether your business knows what information it receives, what access it has and who is accountable for its output.

Ask staff which tasks they are trying to complete faster. Common examples include summarising customer emails, extracting invoice details, drafting tender responses and searching internal procedures. Explain that the initial exercise is about understanding use and reducing exposure, not catching people out.

For each workflow, record:

• The tool, account owner and business purpose.
• The information entered, uploaded or retrieved through integrations.
• Whether it only produces drafts or can change records and send messages.
• Who checks its output and how often it is used.

Give each workflow a business owner. IT can assess access and security, but the relevant manager must decide whether the workflow is appropriate.

Find unapproved AI through several evidence sources

Staff conversations are essential, but they will not reveal every integration. Ask your managed service provider to compare the declared tools against available technical and purchasing records.

Useful evidence can include installed applications, managed browser extensions, identity sign-ins, application consent records, expense claims and network security logs. Check shared mailboxes and automation platforms for connections established by individual staff members.

Be realistic about visibility. A network log may show that someone visited an AI service without revealing what they uploaded. Personal devices and accounts may sit outside managed controls. Missing evidence does not prove there has been no use.

Before introducing monitoring, explain its purpose and scope. Check applicable workplace surveillance and privacy obligations, including state or territory requirements, and obtain advice where needed.

Maintain a register with four statuses: approved, approved with restrictions, under assessment and blocked. Record the decision owner, reason and review date. This makes shadow AI governance a repeatable process rather than a one-off software list.

Set data-handling rules staff can actually follow

A useful AI policy answers a practical question: can I put this information into this tool for this task?

Start with a short decision table and adapt it to your contracts, privacy obligations and information classifications.

| Information | Starting rule | | --- | --- | | Published product information | Use only in approved tools; check accuracy before publishing output | | Internal procedures and working documents | Use only where the approved workflow permits that classification | | Customer, employee or supplier personal information | Require assessment of necessity, access, retention and contractual obligations | | Payroll, financial records or confidential agreements | Restrict to specifically authorised workflows and users | | Passwords, authentication codes and secret keys | Never enter into AI prompts or uploaded documents |

Do not assume removing a name makes a document anonymous. Addresses, transaction details and unusual circumstances may still identify someone.

For each proposed service, check retention, deletion, model-training terms, administrative controls and subprocessors. Confirm where prompts, documents, outputs and logs are processed and stored. A paid subscription is not, by itself, evidence that a tool meets your requirements.

Private Australian hosting is an important deployment choice, but it does not replace access controls or legal assessment. Check whether external model calls, support access or connected services change the data path.

Control access and actions, not just websites

Blocking a risky website may be appropriate, especially during an investigation. However, a website block does not revoke an integration that already has access to business data.

Review application permissions alongside user accounts. An AI connection that can read an entire document library or send email needs closer scrutiny than a tool receiving a small, deliberately selected document set.

Ask your IT provider to:

• Use business-owned accounts, single sign-on and multi-factor authentication where supported.
• Limit access to the records needed for the approved task.
• Restrict user consent to new applications and review existing grants.
• Remove unused integrations and revoke associated tokens.
• Apply supported browser, endpoint and data-loss controls after testing them.
• Include AI services in staff onboarding, role changes and offboarding.

Microsoft 365 controls depend on licensing, configuration and the applications involved. Confirm what your environment can detect or block before relying on it.

Separate permission to prepare a draft from permission to execute an action. For finance workflows, see where humans approve AI-assisted invoice processing. The approval point should come before payment, posting or another consequential change.

Offer an approved alternative for each priority task

Shadow AI governance is more likely to hold when staff have a practical way to complete their work. Start with a narrow workflow that has a clear owner, measurable acceptance criteria and manageable data access.

Tech Engine's managed AI agents run in a private Australian-hosted environment and retain human approval. Relevant alternatives include:

• Order and Data Intake Agent: prepares validated order records, with people approving exceptions and downstream changes.
• AP/AR Automation Agent: matches supplier invoices to records and prepares draft customer invoices for review.
• Knowledge and SOP Agent: provides a controlled, searchable environment for approved procedures and business rules.
• Document Review and Compliance Agent: checks documents against defined criteria and flags exceptions for human review.

Before a pilot, document the inputs, permitted integrations, approval steps and stop conditions. Test missing fields, contradictory records and documents containing instructions that attempt to redirect the agent. Treat retrieved material as data, not authority to change permissions or bypass review.

Give reviewers enough context to make a decision: source records, identified exceptions and proposed changes. Human approval should be an informed control, not a routine click.

For spreadsheet-based work, our guide to Copilot budgeting and forecasting review checks explains why AI-assisted finance output still needs validation.

Establish a response process and review cycle

Tell staff how to report an accidental upload promptly. Record the tool, account, information involved, timing and any permissions granted. Do not ask them to paste the sensitive material into another system to explain the incident.

Your response may involve suspending access, revoking tokens, requesting deletion and preserving relevant evidence. A deletion request does not prove all copies have been removed. Where personal information is involved, assess applicable breach-response obligations rather than assuming every upload is automatically notifiable.

Use the first month to build the register, address the highest-risk access and pilot one approved alternative. Then review new tools, exceptions and integration changes regularly. Track outstanding assessments, excessive permissions and whether staff have adopted the approved workflow.

Make the safer workflow easier to use

Effective shadow AI governance combines clear rules, proportionate technical controls and useful alternatives. Employers retain accountability; their managed service provider helps implement and maintain the controls.

Tech Engine can help identify unapproved use and introduce managed AI agents that integrate with existing systems, run in a private Australian-hosted environment and keep human approval. Call 1300 088 324 or email sales@techengine.au to discuss a suitable starting workflow.