Know the risks

AI can help organisations save time, improve services and make better decisions. But it can also increase existing risks or introduce new risks.

Understanding these risks is the first step to using AI safely and with confidence.

Traditional software follows fixed rules. If you put in the same information, you get the same result every time.

AI works differently. It learns from data and creates outputs based on patterns, not fixed rules.

Because of this, AI can:

• produce unexpected or incorrect results
• reflect or increase bias in its training data
• behave differently depending on how it’s used
• run continuously without natural pauses.

The risks you face depend on how you use AI, who it affects, and how much oversight you have.

Here are some common risks.

Accuracy and reliability

AI can produce outputs that sound confident but are wrong, incomplete or misleading. These errors aren’t always easy to spot.

Bias and fairness

AI learns from data. If that data is biased or incomplete, outputs may unfairly affect certain people or groups. This risk is higher in areas such as hiring, pricing, eligibility or customer decisions.

Privacy and data handling

AI tools often use large amounts of data. Without clear controls, personal or sensitive information may be shared or reused in ways you didn’t expect.

Security

AI tools can introduce new cyber security risks, such as data leaks or unauthorised access. This risk increases when tools connect to business systems or are used outside approved processes.

Legal and compliance

AI can raise issues under privacy, consumer, employment or copyright law. Your organisation is still responsible for meeting legal obligations, even when AI tools are supplied by a third party.

Safety

AI can produce information that sounds reliable but may be wrong. When used in areas such as health, finance or workplace safety, incorrect information can cause harm. 

Reputation and trust

Incorrect or inappropriate AI outputs can damage trust quickly. This is more likely if the issues affect many people before they are noticed.

AI systems can act fast and at scale. When something goes wrong, the impact can grow quickly.

For example:

• inaccurate information could affect hundreds of customers before anyone notices
• a biased system could exclude many qualified applicants.

Small issues can become serious problems if they aren’t found early.

Risk is higher when AI:

• interacts directly with customers or the public
• influences important decisions about people
• runs with little or no input from people
• runs continuously or at scale
• uses personal, sensitive or confidential information.

These situations need stronger controls, clearer accountability and ongoing monitoring.

Early signs of negative impacts include:

• outputs changing without a clear reason
• staff relying on outputs without checking them
• customer complaints about accuracy, tone or fairness
• inconsistent outcomes for similar situations
• unapproved use of AI tools.

Recognising these signs early can help organisations act before harm occurs.

You can screen for AI risks to see which AI systems might present major risks or required greater safeguards. Risks don’t always mean organisations should avoid AI. They show why clear guidance, oversight and safe‑use practices are essential.

Our essential AI practices help organisations manage these risks by:

• deciding who is accountable
• understanding impacts and planning accordingly
• measuring and managing risk
• sharing essential information
• testing and monitoring systems
• maintaining human control.

Knowing the risks isn’t about stopping innovation. It’s about using AI with confidence, care and control.

Learn about other ways to manage risks from AI.