Artificial intelligence is already changing how businesses write, research, analyse information and communicate with customers. Used well, it can save time and help your team focus on higher-value work.
But there is another side to the AI boom: employees using AI tools without the knowledge or approval of the business.
This is known as Shadow AI. It might be someone copying customer information into a personal chatbot, connecting an AI assistant to their work email or using an unapproved tool to summarise a confidential document.
The issue is not that people are trying to do the wrong thing. In many cases, they are simply trying to work faster.
The solution is not to ban every AI tool. It is to build a secure AI workflow that gives your team useful, approved ways to work with AI while protecting business information.
According to Bitdefender’s 2026 Cybersecurity Assessment, 47.4% of organisations have only partial or no visibility into employee AI usage. That makes Shadow AI a significant security blind spot.
Here are five practical steps to help close the gap.
1. Find out how AI is already being used
Before creating rules, find out what is actually happening.
Ask your team:
- Which AI tools do you use for work?
- What tasks do you use them for?
- Have you connected any AI tools to business accounts?
- Do you use personal AI accounts for business tasks?
- What information do you enter into those tools?
- Which AI features are already built into your existing software?
You may discover that AI is already part of everyday work through tools your business has approved. For example, AI features can appear inside productivity suites, meeting platforms, customer relationship systems, browsers and design applications.
This is why Shadow AI is more complicated than simply checking whether someone uses a popular chatbot. AI can be embedded in software without employees always recognising that they are using it.
Create a simple register of:
- Approved AI tools
- Unapproved or unknown tools
- Users and departments using them
- Business purposes
- Types of information being processed
- Any connected business accounts or integrations
You do not need a complicated system to begin. A clear spreadsheet and a few honest conversations can reveal a lot.
The goal is not surveillance or blame. It is visibility. You cannot protect information you do not know is being shared.
2. Classify the information AI should and should not handle
Once you know how AI is being used, decide what information is suitable for each use case.
A simple information classification system could include:
Public information
This is information that is already publicly available, such as published website content, public job advertisements or general marketing copy.
Internal information
This includes everyday business information that should not be shared publicly but may be suitable for approved business tools with the right controls.
Confidential information
This may include pricing, contracts, financial reports, customer records, internal strategies and employee information.
Highly sensitive information
This could include passwords, identity documents, payment details, private health information, legal advice, unreleased business plans or regulated data.
As a general rule, employees should never paste confidential or highly sensitive information into a public or personal AI tool.
It is also important to think beyond the text entered into a prompt. An AI application may be able to access files, emails, calendars, meetings or other connected services. Those permissions need to be reviewed carefully.
Your policy should explain:
- What information can be entered into approved AI tools
- What information must never be entered
- Which tools are approved for business use
- Whether personal AI accounts can be used for work
- How AI-generated content must be checked
- Who is responsible for reviewing new tools
- What to do if information is shared accidentally
Keep the language practical. A policy that nobody understands will not protect your business.
3. Approve tools and control access
A secure AI workflow needs a clear approval process.
When someone wants to introduce a new AI tool, review:
- What data the tool collects
- Where that data is stored
- Whether the provider uses customer data to train its models
- What security and privacy controls are available
- Which integrations and permissions it requests
- Whether user access can be managed centrally
- What happens to the data when the account is closed
- Whether the tool supports your legal and compliance obligations
For businesses using Google Workspace, central administration can help you manage users, devices, sharing settings and security controls from one place. This provides a stronger foundation than allowing employees to connect tools independently using personal accounts.
Access should also be limited to what each person needs. If an AI tool only needs access to a specific folder, do not give it access to the entire company Drive. If a team does not need a particular integration, leave it disabled.
Review access regularly, especially when:
- A team member changes roles
- Someone leaves the business
- A project ends
- A tool changes ownership or pricing
- A new AI feature is added to an existing application
Shadow AI often grows through convenience. Someone connects a tool once, it becomes part of a process and nobody revisits the permissions. Regular reviews help prevent that quiet expansion.
4. Build training into the workflow
Policies and technical controls are important, but your people are still the first line of defence.
Training should show employees how to use AI safely in the work they actually do. Generic warnings are easy to forget. Practical examples are much more useful.
Your training could cover:
- How to recognise an approved AI tool
- How to check whether an AI feature is enabled
- What information must not be shared
- How to remove personal or customer details from a prompt
- Why AI-generated answers need human review
- How to identify incorrect, biased or misleading outputs
- How to check links, attachments and generated code
- What to do after a suspected data disclosure
- How to request approval for a new AI tool
For example, instead of entering a customer’s full complaint into a public tool, an employee might remove names, account numbers and identifying details before asking for help with a draft response.
Training also needs to be ongoing. AI tools and features are changing quickly, so a one-off session is unlikely to be enough.
At Cloud Computer Company, training is baked into the way we approach technology projects. Whether your team is learning Google Workspace or adopting new cloud-based workflows, people need clear guidance and the confidence to use the tools properly.
5. Monitor, review and improve
A secure AI workflow is not something you set up once and forget.
Schedule regular reviews to check:
- Which AI tools are approved
- Whether new tools or features have appeared
- Whether staff are following the policy
- Which accounts have access to AI integrations
- Whether sensitive information is being handled correctly
- Whether security alerts or unusual activity have been reported
- Whether the workflow is still useful for employees
Make it easy for staff to ask questions. If the approval process is slow or unclear, people may work around it.
It is also worth creating a straightforward incident process. If someone accidentally uploads confidential information to an unapproved AI tool, the first response should be quick and calm:
- Stop using the tool.
- Record what information was shared.
- Disable access or integrations where possible.
- Notify the right internal contact.
- Assess whether customers, suppliers or regulators need to be informed.
- Update training or controls to reduce the chance of it happening again.
A supportive response encourages early reporting. A blame-focused response can cause people to hide mistakes, making the problem worse.
Secure AI does not have to mean complicated AI
Small businesses often worry that AI governance will require a large security team, expensive software and endless paperwork. It does not have to.
Start with the basics:
- Know which tools your people are using.
- Define what information is safe to share.
- Approve tools deliberately.
- Limit access.
- Train your team.
- Review the process regularly.
The right approach will depend on your systems, industry, team and risk profile. That is where experienced support can help.
Cloud Computer Company provides founder-led, personal service with end-to-end ownership across consultancy, deployment, training and ongoing support. We take the time to understand how your business works, recommend practical options and explain the costs clearly with transparent pricing.
If you are already using Google Workspace, our Google Workspace health and security checkup can help identify security risks, access issues and opportunities to improve your overall security posture.
You can also book a free consult to discuss your AI workflow, cloud security and next steps. No jargon, no pressure and no one-size-fits-all advice.
“47.4% of organisations have only partial or no visibility into employee AI usage. A secure AI workflow starts with knowing which tools your team is using: and what information they are sharing.”
About Mathew Hoffman
Mathew Hoffman started his career in IT in 1981 and has held senior roles with State Bank of NSW, Minet Australia, Wilhelmsen Lines and Rothmans of Pall Mall. He also worked on technology supporting the Sydney 2000 Olympics.
Since 2001, Mathew has provided IT consultancy to small and medium businesses. He became one of the original Google Partners in 2008 before re-branding the business as Cloud Computer Company in 2017.
Based in Noosa, Mathew enjoys cricket, which he has played and coached in Sydney and on the Sunshine Coast, as well as spending time with family, the beach and golf.
