AI in Business: New Risks, Evolving Insurance, and What You Need to Know Now

AI in Business: New Risks, Evolving Insurance, and What You Need to Know Now

Businesses are adopting artificial intelligence (AI) tools at pace, often without a clear understanding of the liability that comes with them. AI driven decisions can cause real harm, including algorithmic bias affecting lending or hiring, data breaches tied to training data, intellectual property disputes over whether training data was licensed, and regulatory breaches.

Until recently, the concern was that insurance had not caught up. That has changed. Through 2026, insurers have moved quickly to decide where AI risk sits, and in many cases the answer is that it sits outside the policy. Businesses using AI should understand how they are using it and review their cover with their adviser.

Why AI Introduces New Liability

AI creates liability at speed and scale. A single algorithmic error in lending decisions can affect thousands of customers simultaneously. The impact is multiplied.

The second challenge is opacity. Machine learning models often work as 'black boxes'. Even their creators can't always explain why a specific decision was made. 'The algorithm decided' isn't a legal defence for unfair treatment.

Bias is built into training. If a hiring dataset historically favoured men, the model learns that preference and perpetuates it at scale. A lending AI trained on data where certain age groups were less likely to repay will discriminate against those age groups automatically. This isn't intentional bias. It's the algorithm reproducing historical patterns.

Third-party dependency is a major risk. Most businesses use cloud-based AI platforms like ChatGPT or cloud ML services. You don't see or control how the model was trained or what data it uses. When you feed proprietary information into ChatGPT, that data may be retained or used to train other models. Your data becomes part of a system you no longer control.

Regulatory risk is emerging fast. Regulators are moving quickly on AI governance. Financial regulators expect transparency in algorithmic decision making. Fair Work bodies are monitoring the algorithmic management of employees. Privacy authorities are scrutinising the use of personal data in AI training. Businesses using AI to make material decisions should expect regulatory scrutiny.

Gaps in Current Insurance

Your existing insurance may not cover AI-specific harms. Cyber liability covers data breaches and network attacks. Does it cover data misuse by an AI model? Unclear. Does it cover platform failure? It depends on the policy wording. Professional indemnity covers professional negligence. Does it cover algorithmic bias in advice? Probably not explicitly. Employment practices liability covers employment disputes. Does it cover hiring discrimination by an algorithm? The position is still evolving.

If you're using AI, gaps are likely to exist in your current policies. That's why you should talk to your insurance adviser now to make sure you have the right type and amount of cover.

General Advice Warning 
This communication including any weblinks or attachments is for information purposes only. It is not a recommendation or opinion, your personal or individual objectives, financial situation or needs have not been taken into account. This communication is not intended to be a constitute personal advice. We strongly recommend that you consider the suitability of this information, in respect of your own personal objectives, financial situation and needs before acting on it. This document is also not a Product Disclosure Statement (PDS) or a policy wording, nor is it a summary of a particular product’s features or terms of any insurance product. If you are interested in discussing this information or acquiring an insurance product, you should contact your insurance adviser to obtain and carefully consider any relevant PDS or policy wording before deciding whether to purchase any insurance product.

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