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AI Risk Is Creating New Questions for Professional Cover

Why businesses using automated tools should check where liability sits

AI Risk Is Creating New Questions for Professional Cover?w=400

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A fresh warning from Australian medical indemnity underwriter Tego has highlighted a risk that many businesses are only beginning to confront: artificial intelligence may not fit neatly inside existing insurance categories.
As AI tools become embedded in diagnosis, administration, client advice, document drafting, fraud detection and customer service, the question is no longer simply whether a mistake occurred.
It is also who made the decision, who controlled the system and which policy should respond.

Tego has described this as a potential stack gap. In practical terms, a claim involving an AI-enabled decision could trigger arguments between multiple insurance lines. A professional indemnity or medical malpractice policy may focus on the professional’s conduct. A cyber policy may require a network or data event. A technology errors and omissions policy may be written around software performance, but exclude certain types of harm. Product liability wording may not clearly address whether an AI model is a product in the traditional sense.

For small businesses, consultants and technology providers, the message is clear: using AI does not remove professional responsibility. If an automated tool helps produce advice, assess a client file, prioritise treatment, screen applications or draft recommendations, the business still needs to understand how its insurance would respond if the output is wrong. That is especially important where clients rely on your expertise and could allege financial loss, delay, negligence or breach of duty.

The issue is not limited to healthcare. Accountants, engineers, migration advisers, designers, financial service providers, HR consultants, marketing agencies and SaaS firms are all experimenting with AI-assisted workflows. Some are using public tools, while others rely on embedded systems supplied by vendors. Either way, risk can sit across several layers: the end user, the professional firm, the software provider, the underlying model provider and any data sources used to train or prompt the tool.

Before adopting AI in client-facing work, businesses should take a disciplined approach:

  • Map where AI is used and whether it influences professional judgement or only supports administration.
  • Keep human review and approval processes clearly documented.
  • Check policy wording for AI exclusions, technology services exclusions, bodily injury exclusions and cyber-only triggers.
  • Ask whether your current professional indemnity limit remains appropriate as automation increases scale and speed.
  • Compare suitable cover options before assuming an existing policy will respond.

This development is also a reminder that professional indemnity insurance is not a set-and-forget purchase. As business models evolve, cover should evolve with them. A policy arranged before widespread AI adoption may not reflect today’s exposure, particularly if your work now includes automated recommendations, data analysis or system-driven decisions.

A useful next step is a policy review with professional indemnity insurance brokers who understand both your occupation and your technology use. AI can improve efficiency, but it also changes the claims conversation. Knowing where liability sits before something goes wrong is far safer than discovering the gap after a client dispute.

Published:Monday, 22nd Jun 2026
Author: Paige Estritori

Please Note: We do not endorse any specific products or companies. Some content is sourced from third parties, including press releases, and may not be independently verified for accuracy or completeness.

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Knowledgebase
Moral Hazard:
The concept that individuals may take on more risk when they do not bear the full consequences of that risk, often relevant in insurance scenarios.