In our 'Contentious AI' insight series we unveil key facts about the development, adoption and use of AI and how it can become contentious. In this article, we outline critical competition and consumer law risks associated with the use of AI and suggest key actions to manage these risks.
AI creates real commercial opportunity. However, the integration of AI brings with it a risk of increased scrutiny. Regulators are watching how AI is developed, how it is used, and how it is embedded in the products and services that businesses sell.
In late 2025, the ACCC released a snapshot report that built on its multi-year Digital Platform Services Inquiry. It flagged concerns ranging from the competitive implications of AI-driven market changes, risks associated with the increasing use of AI agents, and a range of consumer law issues arising from the increased use of AI in consumer-facing business practices.
However, a key takeaway is that few of these risks are genuinely novel. As Treasury observed in its October 2025 review of AI and the Australian Consumer Law, the existing consumer law framework is largely fit for purpose.
AI is accelerating familiar legal risks, not creating entirely novel legal risks. With the ACCC's 2026-27 priorities targeting manipulative and false practices in digital markets, and the government moving to prohibit unfair trading practices, the direction of travel is clear.
Competition risks
As companies increasingly integrate third-party AI tools across their operations, it is critical to test and understand what is happening 'under the hood' — to ensure the use of AI products accounts for potential regulatory scrutiny and enforcement risk.
The most immediate competition law risk for many businesses is likely to arise from third-party pricing tools. For businesses that use models to price products, it is important to carefully interrogate any third-party pricing tools that are used within the business – for example, as an input into a pricing engine. This includes how the third-party product will use (and potentially monetise) your organisation’s data, who that data will be shared with and in what form, and the granularity of data outputs.
The use (and misuse) of commercially sensitive data is not a new issue. However, AI is likely to increase the ways in which data can be leveraged and the time in which that can occur. To provide a recent example, rental management software supplier, RealPage, has faced public and private litigation in the United States, including by the Department of Justice, concerning allegations that it collated sensitive competitor data and presented pricing recommendations to customers.
RealPage supplies cloud-based property management software. Among its functions it included rent-setting tools that aggregated non-public data from various sources and presented a 'recommended' level of rent (or increase in rent) to its customers. The allegation was that RealPage’s customers agreed to provide current and forward-looking pricing information, were aware that their data had been pooled, and that RealPage then took steps to monitor customer compliance with its price recommendations. Despite settling with the DOJ, both RealPage and some customers were exposed to private litigation, and private class actions by renters has resulted in material settlements with claimants.
What businesses should do to manage potential competition law risks:
(a) Invest in training your team — a strong competition compliance culture is your first and most effective line of defence.
(b) Understand the data that AI or data-led products are leveraging, the decisions they are making, and how consumers might perceive the way in which data (including their own personal data) is being used.
(c) Recognise that software tools can potentially create liability for both the developer and its customers, and apply an appropriate risk lens when testing for risk that might arise from purchasing and integrating that product.
(d) Allocate risk — if AI is built into the goods or services you supply, ensure that responsibility is clearly documented.
Consumer law risks
The ACCC will generally pursue a consumer law avenue where one is available — generally, enforcement action under the Australian Consumer Law is more straightforward to establish. With new restrictions against unfair trading practices currently being considered by parliament, the regulator's enforcement toolkit is likely to further expand in the coming years.
Two risk areas warrant particular attention – what businesses say about AI and what AI might say on a business' behalf.
First, considering the focus on AI at present, we expect that representations about the use or integration of AI-enabled products are likely to be subject to particular scrutiny. The ACCC is squarely focused on any gap between what consumers are told a service will do and what the back-end systems can actually deliver. This will include service offerings that are framed as leveraging AI.
The ACCC is continuing to target instances where there is a mismatch between what a product or service delivers and how that product has been promoted to consumers. A mismatch can, for example, arise not because the business set out to mislead consumers, but rather because systems evolved, something failed in the back end, or marketing collateral was not updated to account for product changes. AI does not remove that risk, and in some cases it can exacerbate it. We have covered this issue in detail in our previous article in this series, The legal risk of AI washing.
Second, in terms of AI-led representations, as businesses increasingly look to leverage AI agents to help manage customer-facing enquiries, there is increasing focus on the extent to which businesses will be held to be accountable for representations that have been made by an agent. In North America, an airline has been found to have made a negligent misrepresentation to one of its customers who relied on incorrect information that was provided to them by a chatbot.
In that case, the tribunal found that the airline had not taken reasonable care to ensure that the chatbot was providing accurate information. Even though correct information was available elsewhere on the airline’s website, the customer was not obliged to verify the information that had been provided by the AI agent. While this was only a small claims decision, it signals what we expect will be an increasing focus on these types of issues, both by regulators and private litigants.
Finally, following an ACCC-led advocacy campaign, parliament is currently considering an expansion to the regulator's powers under the Competition and Consumer Amendment (Unfair Trading Practices) Bill 2026. If passed, this Bill would introduce an unfair trading practices prohibition into the Australian Consumer Law, potentially from 1 July 2027.
The objective is to create a general prohibition that would capture manipulative or distortive conduct that is likely to cause consumer detriment (financial or otherwise).
The proposal is that a contravention would require two elements to be satisfied:
- the conduct must unreasonably manipulate the consumer or unreasonably distort the environment in which a consumer makes a decision; and
- it must cause, or be likely to cause, a detriment.
The ACCC has framed this additional prohibition as a mechanism principally directed at addressing so-called 'dark patterns' and other sales techniques, primarily in online settings. At present, these types of tactics will only create risk where they breach the general prohibitions against misleading or deceptive conduct. However, what has been proposed will potentially have broad reach. The proposed unfair trading practice prohibition has, for example, been flagged as a potential tool to address consumer harm arising from AI-driven commercial interactions.
Questions remain about how the prohibition might apply to AI-enabled strategies, including, for example, personalised promotions. Businesses should expect that the ACCC will seek to leverage all tools available to it, including to address consumer issues arising in new settings, including AI.
What businesses should do to manage potential consumer law risks:
(e) Ask what representations are made and how accurately they reflect the product or service (if there is a mismatch).
(f) Consider what guidance or recommendations the product is actually making, and when queries need to be escalated.
(g) Test what guardrails are in place regarding inputs, the scope of AI use, and the extent of human oversight, ensuring that the concept of 'compliance by design' is firmly embedded.
Coming up next
The insight series will expand to explore the following topic next:
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