What Businesses Need to Consider for Using AI Securely

Artificial intelligence is now part of everyday business. Teams are using AI to draft emails, summarise documents, analyse data, support customers, automate admin, write code and speed up decision-making.

Used well, AI can save time, reduce repetitive work and help businesses achieve growth and operate more efficiently. But like any technology that touches business data, customer information, internal systems or staff workflows, it also needs to be used carefully.

The opportunity is significant, but so is the need for structure. AI should not be treated as a harmless add-on or a quick productivity shortcut. It should be treated as a business system that needs the right security, privacy, governance and operational controls around it.

For many organisations, the challenge is not deciding whether AI has value. It is knowing how to introduce AI securely, practically and responsibly.

Start by understanding where AI is already being used

Before your business can manage AI securely, you need to understand how it is already being used across your organisation.

This could include approved tools such as Microsoft Copilot, ChatGPT Enterprise, Gemini, Claude, AI-powered CRMs, ticketing platforms, reporting tools and automation platforms.

It could also include informal AI use, such as staff pasting content into free AI tools, using browser extensions, installing AI meeting assistants, or connecting third-party apps to business systems without approval.Many SaaS systems also have AI integrated into them by default now, making it important to review what is being used, potentially inexplicitly. Importantly, review what access these have to existing organisational data in the default settings.

This is often referred to as shadow AI. It usually does not come from bad intentions. In most cases, staff are simply trying to work faster or make their day easier. The risk is that confidential information, customer data, intellectual property or internal documents may be entered into systems the business has not assessed.

A practical starting point is to create an AI register. This does not need to be complicated. It should list what AI tools are being used, who owns them, what they are used for, what data they access, whether they are approved, and when they should next be reviewed.

Your business can’t secure what you don’t know exists.

Set clear rules around business data

One of the most important questions your business needs to ask is‘What information can staff safely enter into AI tools’.

Without clear guidance, staff may make their own judgement calls. That can create risk, especially when AI is used with client information, internal documents, financial data, HR matters, contracts, passwords, API keys, source code or security-related information.

A business should have a clear AI data policy that explains what is usually safe, what needs approval and what should never be entered into an AI system.

For example, public marketing information may be relatively low risk. A de-identified draft email may be acceptable with caution. But personal information, confidential client records, legal matters, commercial documents, financial records, health information, system credentials and cybersecurity configurations should be treated very carefully.

After all, we haven’t forgotten unintentional slip-ups from high-level employees at Samsung leaking sensitive company data in 2023.

Apply strong access control

AI does not replace cybersecurity basics. In many cases, it makes them more important.

If an AI tool is connected to email, files, SharePoint, CRM records, support tickets, customer data or internal systems, access control becomes critical. At a minimum, your business should:

• Only give staff access to the tools and data they need for their role,
• Limit admin accounts,
• Remove former staff quickly, and
• Avoid shared accounts.

Where possible, AI tools should be protected through single sign-on, multi-factor authentication and centralised identity management. This helps the business maintain visibility and control over who is using AI, what they can access and how access is removed when roles change.

This becomes even more important when AI is used for automation. A chatbot that only drafts text has one level of risk, whereas an AI-powered workflow that can read emails, update records, create tickets, send messages or trigger business processes has a much higher level of risk. The more an AI system can access or act on, the stronger the controls need to be.

Understand AI-specific security risks

Some AI risks are simply new versions of familiar cybersecurity problems. Others are more specific to how AI systems work.

Prompt injection

This is where a malicious or carefully crafted instruction attempts to manipulate an AI system into ignoring its usual rules or behaving in an unintended way.

For a business, this becomes more serious when AI is connected to other systems. Imagine an AI assistant reading an email that contains hidden instructions telling it to ignore previous rules, reveal confidential information or take an unauthorised action. If the AI has too much access or too much authority, the issue can move from a poor output to a genuine business incident.

Data poisoning

This occurs when the information used to influence an AI system is incorrect, manipulated or unreliable, which can then affect the quality of the outputs.

For most businesses, this may not involve training a large AI model from scratch. But it can still matter if AI is connected to internal knowledge bases, SharePoint folders, policy libraries, support documentation, CRM notes or helpdesk histories. If the information feeding the AI is wrong, outdated or compromised, the outputs may be wrong too.

AI hallucinations

AI systems can produce information that sounds convincing but is inaccurate, incomplete or misleading. In a business context, that can create real problems if staff rely on AI outputs without checking them.

Review AI outputs by risk

Low-risk uses, such as brainstorming internal ideas or summarising non-sensitive notes, may need minimal review.

Medium-risk uses, such as drafting client-facing content or internal procedures, should be checked by a person.

High-risk uses, such as legal, financial, HR, medical, cybersecurity or compliance-related content, should require subject matter review before being used.

The important thing is to identify areas where an AI output has higher impact on a person, customer, payment, system, legal position or business decision, and requires more human oversight as policy.

Review AI vendors before connecting business data

Most businesses will use AI through third-party platforms rather than building their own systems. That makes vendor review a major part of secure AI adoption.

Before connecting an AI tool to business data, organisations should ask practical questions:

• Where is our data stored?
• Can our data be used to train the model? And, can we opt out?
• How long is data retained? Can it be deleted?
• What security controls does the platform support? Does it offer multi-factor authentication and single sign-on? Are logs available?
• Who are the vendor’s sub-processors? What happens if there is a breach or outage?

These questions are not just technical. They affect privacy, compliance, operations and customer trust. While a tool may look useful, if it cannot meet the business’s security and data protection expectations, it may not be suitable for use with sensitive information.

Put guardrails around AI automation

AI automation is where the opportunity becomes especially powerful, but also where risk can increase quickly.

When AI is used to automate repetitive business processes, it may be able to read information, make recommendations, draft responses, move data between systems, update records or trigger actions. This can save significant time, but it also means mistakes can scale quickly if the workflow is not designed properly.

Secure AI automation should include guardrails such as human approval for high-impact actions, least-privilege permissions, clear error handling, logging, testing, rollback processes and limits on what the automation can do without review.

For example, it may be reasonable for AI to draft a client email. But sending that email, updating a financial record, changing customer information or making a decision that affects service delivery may require human approval.

The safest AI automation is not necessarily the one that removes people from the process entirely. It is the one that removes unnecessary manual effort while keeping the right people involved at the right points.

Monitor, review and prepare for incidents

Businesses should regularly monitor how AI is being used, review whether tools are still fit for purpose and check whether outputs remain accurate and useful. AI tools, vendor terms, model behaviour and business use cases can all change over time.

It is also important to think about what happens when something goes wrong. AI should be included in incident response and business continuity planning.Your business should know who is responsible, how the issue will be contained, what records need to be reviewed, who needs to be notified and how the organisation will continue operating if the AI system is unavailable.

 

Secure AI adoption is built on strong cyber security foundations

AI may feel new, but many of the controls needed to secure it are familiar (multi-factor authentication, least privilege, logging, backups, staff training, supplier review, incident response and clear governance).

This is why AI security should not sit separately from cybersecurity. It should be part of the same broader approach to protecting business systems, data and operations. Your business doesn’t need to be afraid of AI, but you do need to be intentional about how it is introduced.

The best approach is to start with clear visibility, practical policies, secure configuration and well-designed workflows. From there, AI can become a genuine business advantage rather than an unmanaged risk.

 

 

For businesses looking to adopt AI and automation securely, the Australian Cyber Security Centre’s guide on engaging with artificial intelligence is a useful resource for understanding key considerations. But turning that guidance into practical business systems, secure workflows and real-world implementation requires the right expertise.

Sydney ICT helps businesses adopt AI and automation in a way that is secure, practical and aligned with their operations. From assessing AI tools and securing Microsoft 365 environments through to designing safe automation workflows and implementing cybersecurity controls, our specialists can help your business use AI with confidence.