Artificial intelligence is transforming the way businesses work.
From drafting emails and summarising documents to creating reports and analysing information, AI tools can significantly improve productivity. However, they also introduce new data security risks that businesses cannot afford to ignore.
For SMBs, the challenge is often not the technology itself but how employees use it. A helpful AI tool can quickly become a security concern if sensitive information is shared without proper controls, permissions, or guidance.
Microsoft 365 Copilot is a good example. When deployed correctly, it allows users to work within the security framework of Microsoft 365. However, many employees also experiment with other AI tools that sit outside your managed environment, creating additional risks that may be difficult to monitor or control.
Why AI Changes the Data Security Landscape
Traditional data security focused on three core questions:
- Who can access the data?
- Where is the data stored?
- How is the data shared?
Those questions still matter, but AI introduces a new layer of complexity.
AI encourages users to copy, paste, summarise, and transform information quickly. As a result, sensitive data can easily move into prompts, chat histories, generated content, or third-party applications without employees fully considering the implications.
For example, a staff member who would never email a confidential document to a personal account might paste sections of that same document into an AI assistant to improve wording or create a summary.
The action feels harmless because the tool is designed to be helpful and convenient.
That is exactly why clear rules and controls are essential.
The Biggest AI Security Risks for SMBs
Data Leakage
Data leakage is one of the most significant risks associated with AI adoption.
This can occur when employees enter:
- Customer information
- Contract details
- Pricing data
- Financial information
- Internal business plans
- HR records
into AI platforms that have not been approved for handling sensitive information.
Once data is shared with the wrong platform, businesses can lose visibility and control over how that information is stored, accessed, or reused.
Poor Access Control
Access permissions become even more important when AI tools are involved.
If users already have access to more information than they need, AI can make those permissions more visible by surfacing content from across systems and repositories.
In Microsoft 365 Copilot, existing permissions remain in place. This is beneficial from a security perspective, but it also means over-permissioned folders and shared locations can create greater exposure.
AI does not fix poor access management. It often highlights it.
Shadow AI
Shadow AI refers to employees using AI tools without approval, oversight, or security review.
Examples include:
- Using public AI chatbots for work tasks
- Uploading company files to external AI platforms
- Using browser-based AI tools without IT knowledge
- Connecting unauthorised AI services to business systems
Employees generally do this to improve productivity rather than cause harm.
The problem is that the business may have no visibility into:
- Which tools are being used
- What data is being shared
- Where information is being stored
- How generated content is being used
Unclear Data Handling Rules
Many employees simply do not know what information can safely be entered into AI tools.
Questions often arise around:
- Client names
- Financial figures
- Contract drafts
- Internal reports
- Commercially sensitive information
Without clear guidance, employees make their own judgement calls, leading to inconsistent and potentially risky decisions.
How Data Leaks Commonly Occur
Most data leaks do not begin with a major security incident.
They often start with a simple attempt to save time.
Common examples include:
- Pasting a client proposal into an AI assistant for editing
- Uploading a spreadsheet for analysis
- Asking a chatbot to summarise a contract
- Sharing customer information to generate a report
- Using AI tools to rewrite internal communications
While these activities may appear harmless, they can expose sensitive information if the platform has not been approved for business use.
Another common issue arises when AI applications are connected directly to:
- Cloud storage
- Email systems
- Collaboration platforms
- Document repositories
Without careful review, these integrations may gain access to far more information than intended.
A simple question should always be asked:
Did we mean to give this tool access to all of that data?
The Security Controls That Matter Most
Review Access Permissions
Start by ensuring employees can only access the data they genuinely need.
Review:
- Shared folders
- Teams channels
- Document libraries
- Departmental repositories
Strong access controls become even more important as AI tools gain visibility into organisational content.
Approve Specific AI Tools
Employees need clear guidance.
If Microsoft 365 Copilot is approved, say so.
If certain public AI tools are not approved, communicate that clearly as well.
People are far more likely to follow simple rules than vague recommendations.
Define Data Handling Rules
Every business should establish clear guidance on:
- Information that must never be entered into AI tools
- Data that can only be used within approved platforms
- Content that requires management approval before use
- Situations where IT or security teams should be consulted
Simple rules are more effective than overly complicated policies.
Provide Practical Training
Training should focus on real-world examples rather than technical theory.
Show employees:
- What safe AI use looks like
- How to identify risky behaviour
- Which tools are approved
- When human review is required
When staff understand the reasoning behind the rules, adoption tends to be both safer and more effective.
Monitor Usage
Businesses do not need to monitor every action.
However, they should maintain visibility over:
- New applications
- Unusual sign-in activity
- Broad permissions
- Unauthorised integrations
- Unusual sharing behaviour
Monitoring helps identify potential issues before they become significant security incidents.
What a Good AI Policy Looks Like
An effective AI policy should be concise, practical, and easy to understand.
Employees should be able to quickly find answers to questions such as:
- Which AI tools are approved?
- What information must never be entered into prompts?
- Who approves new AI tools and integrations?
- What should employees do if they are unsure?
The policy should also align with broader security practices, including:
- Access control
- Device management
- Email security
- Data retention
- Information governance
Good AI governance is about consistency, not complexity.
The goal is not to prevent employees from using AI.
The goal is to ensure they use it safely and responsibly.
Is Microsoft 365 Copilot Enough?
Microsoft 365 Copilot offers advantages because it operates within your existing Microsoft 365 environment and respects organisational permissions.
However, simply deploying Copilot does not automatically solve every security challenge.
Businesses should still review:
- User permissions
- Data classification
- Information governance
- Access controls
- User behaviour
Security depends as much on the underlying environment as it does on the AI tool itself.
Final Thoughts
AI offers significant productivity benefits for growing businesses, but it also creates new pathways for sensitive data to move beyond traditional security controls.
The greatest risks often come from everyday actions, not deliberate misuse. A copied document, a shared spreadsheet, or an unapproved AI tool can all create exposure if proper controls are not in place.
The most successful organisations treat AI as part of their wider security strategy. By establishing clear policies, controlling access, approving trusted tools, and educating users, SMBs can embrace AI’s benefits while reducing unnecessary risk.
The objective is simple: enable innovation and productivity without losing control of your data.