AI Security Risks for Business: 5 Ways AI Can Increase Cyber Risk (and How to Reduce It)
AI is already creeping into day-to-day work. People use it to draft emails, summarise documents, analyse data, and speed up customer responses.
This article covers five practical AI security risks for business, and what you can do to reduce them without killing productivity.
Direct answer (the skimmable bit)
The biggest AI security risks for most UK businesses are: staff pasting sensitive data into public AI tools, more convincing phishing and impersonation, “shadow AI” use with no visibility, insecure AI-generated code/automations, and criminals using AI to scale cyber attacks.
Reduce the risk with a clear policy, approved AI tools (with business controls), identity and access controls, monitoring/visibility, and human review for anything that can impact systems or sensitive data.
If you only do three things: set clear “never paste” rules, make the safe AI tool the easy option, and strengthen identity/email controls.
1. Staff Share Sensitive Information with Public AI Tools
One of the most common AI risks isn't the technology itself - it's how people use it.
Employees often use tools like ChatGPT, Copilot, Gemini, or other AI platforms to speed up their work. The problem starts when someone copies and pastes confidential information into a tool without understanding where that data may go, how it’s stored, or who else could access it.
This information could include:
- Customer details (including personal data)
- Financial data
- Internal business documents
- Contracts and legal information
- Intellectual property
- Security-related information (configs, incident details, credentials)
Even a well-intentioned employee can accidentally create a data breach simply by asking an AI assistant to help summarise a document or analyse sensitive information.
Controls to put in place:
- Create a clear AI usage policy (what's allowed, what's not, and why)
- Train employees on "never paste" categories (personal data, credentials, client-sensitive info, security detail)
- Use business-grade AI apps where appropriate, and give people an approved alternative (otherwise you'll just drive it underground)
- Restrict access to approved AI applications
- Make it obvious where staff can safely use AI (approved tools, approved use-cases, approved data types)
2. AI Makes Phishing and Impersonation More Convincing
Phishing used to be easier to spot. Poor grammar and odd phrasing gave attackers away.
You’ll see messages that are:
- More believable
- Better targeted
- Grammatically clean
- Harder to identify at a glance
3. Shadow AI Creates Unmanaged Security Gaps
Most organisations have dealt with shadow IT. Shadow AI is the same problem with higher speed and more data involved.
The result is a growing set of unmanaged tools with unknown data handling, unknown access controls, and unknown integrations.
Quick actions:
- Establish approved AI platforms (make the safe route the easy route)
- Maintain visibility over software usage (so you know what’s being used)
- Create basic AI governance: who approves tools, what checks happen, where decisions are recorded
- Review and audit new tools regularly, especially those with integrations into email, file storage, CRM, or ticketing
You can't secure what you don't know exists.
4. AI-Generated Code, Scripts, and Automations Can Introduce Security Problems
AI can accelerate development and automation. It can also produce outputs that look correct but contain flaws.
- Security vulnerabilities
- Poor practices (hard-coded secrets, unsafe defaults)
- Outdated libraries or insecure patterns
- Misconfigured permissions
- Missing error handling (which creates reliability and security problems)
If that makes it into production, it can create genuine openings for attackers.
This isn’t just for “software companies”. Many businesses now use AI to build quick scripts, Power Automate flows, integrations, and admin tooling. Those are still systems, and they still need review.
Security controls to add:
- Don’t deploy AI-generated code or automations without human review
- Treat automations like production changes: peer review + testing + rollback plan
- Run security testing before implementation (even basic checks are better than none)
- Keep human oversight for critical processes (finance, identity, access, customer data)
- Stick to secure development practices regardless of who/what wrote the first draft
5. Cyber Criminals Are Using AI Against You
Perhaps the biggest shift is that attackers are adopting AI just as quickly as businesses.
Attackers are using AI to:
That lowers the barrier to entry and increases the volume and sophistication of attacks. For IT teams, it means the threat landscape moves faster — and “set and forget” security doesn’t hold up.
- Continuously monitor your IT environment (so you can spot issues early)
- Patch and update consistently (reduce easy wins for attackers)
- Use modern threat detection where it matters most (email, identity, endpoints)
- Regularly review and strengthen your security posture (don’t wait for an incident)
AI Doesn't Have to Be a Security Risk
AI can bring real productivity gains. The key is using it deliberately.
If you put the basics in place: clear policy, user training, visibility, approved tools, and sensible controls; you can get the benefits of AI without opening new security holes.
AI is here to stay. The real question is whether your business uses it securely.
Frequently asked questions
Can staff use ChatGPT safely at work?
They can, but only with clear rules. Treat public AI tools as not suitable for sensitive data unless you have an approved business setup and you understand the tool’s data handling. The safest baseline: don’t paste personal data, client-sensitive information, credentials, or internal security details into public tools.
Shadow AI is when staff use AI tools without approval from IT or management. It creates security and compliance gaps because the business can’t see what tools are being used, what data is being shared, or what those tools integrate with.
What’s the biggest AI security risk for most businesses?
For most organisations, it’s data leakage (people pasting sensitive information into AI tools) closely followed by more convincing phishing/impersonation.
How do we stop staff using unapproved AI tools?
Blocking alone rarely works. The most effective approach is:
- provide an approved AI tool that meets the need, and
- set clear rules and training, and
- monitor usage so you can respond early.
Do we need a separate AI security policy?
In most cases, yes, even if it’s short. A good AI policy clarifies what tools are approved, what data must never be shared, and who signs off new tools and integrations.
Need a hand getting the controls right?
If you’re not sure whether your current security posture is ready for AI, the sensible next step is a practical review: what tools are being used, what data is at risk, and which controls will reduce exposure fastest.
If you want, get in touch and let us know what AI tools your teams are using (or suspect they’re using), and what your environment looks like (Microsoft 365, Google Workspace, mix, etc.), and we'll suggest a realistic “minimum viable controls” checklist for an IT Manager to implement.