Preventing Product Liability Disputes with AI

There has been a growing range of product liability claims in many jurisdictions. In addition to conventional sectors that have had relatively high numbers of these claims, such as medical devices, food safety, electrical products and cosmetics, there has been a recent rise in product liability claims pertaining to technological devices and automobiles.

The rise of e-commerce has also seen expanding areas of product liability. COVID-19- has also brought about new types of product liability claims in relation to PPE and products that claim to treat COVID-19 symptoms. Policymakers in many jurisdictions have sought to empower consumers to bring claims more effectively against companies.

In the US, 46 states have enforced strict liability for product defects against manufacturers. This means that fault on the manufacturer’s part is not required to establish liability Even where customers were aware of product defects, such awareness is insufficient to absolve businesses of liability. In 2020, US companies spent an average of US$667,390 on product liability defence costs and cost containment expenses. Comparable protection for product liability can be found in consumer rights legislation in the UK and the EU.  

The above trends highlight the importance of preventing product liability lawsuits for companies. In addition to the costs and time involved in such litigation, resultant negative publicity can have a lasting and detrimental impact on a company’s brand, goodwill, and market share. This post considers how companies can enhance risk management processes for product liability through proactive customer engagement with the help of AI tools. This strategy focuses on early intervention and dispute prevention before product liability risks escalate into damaging lawsuits.

Types of product liability claims

Claims for product liability typically fall into four categories:

(1)  Defective manufacture – Relates to errors that occur during the manufacturing process, such as problems in production which render the injury-causing product different from its intended design. Examples include faulty vehicle breaks, electronic appliances with improperly installed electrical wiring, or furniture that is falsely assembled.

(2) Defective design – Relates to product designs that contain inherent dangers or defects, even if it is manufactured according to design specifications. Examples include vehicles with system faults that make it prone to stalling, safety helmets that break from minimal impact, or electric blankets with a high risk of electrocution.

(3)  Failure to provide adequate warnings or instructions – This type of claim commonly involve products that require extra precaution in their use, or contain dangers that may not be obvious to the user. Examples include heaters that are packaged without sufficient warning about its surface heat, or medicine that is packaged without warning labels of its side effects.

(4) Breach of conditions and warranties  – Relates to products that fall short of written warranties from advertising or instruction manuals. In the US, the warranty of merchantability is implied in contracts for the sale of goods, which specifies that the product is fit for the intended purpose , or if the seller knows that the buyer will be using the product for a certain purpose. Likewise, in the UK, the Consumer Rights Act (CRA) 2015 also provides for certain implied terms in consumer contracts. For example, the implied terms that products are of ‘satisfactory quality’ (Section 9 CRA) , ‘fit for particular purpose’ (Section 10 CRA)  and matches the ‘product description and sample’ (Section 11 CRA)  cannot be contractually excluded.

Approaches to identifying and mitigating against risk

When a product liability claim arises, the company will generally need to investigate the related risks, seek legal advice, institute product recalls, disseminate product warnings and comply with relevant regulatory reporting obligations. These obligations can drain the company’s resources and redirect employees away from profitable projects. Having an effective mitigating strategy can minimise the impact on company resources. Different steps can be taken by businesses and manufacturers to avoid and mitigate product liability claims, which include:

(1) Product safety committees – To oversee the company’s product safety policies with a cross-departmental working group comprising of legal advisors and executive management and a product safety manager. These working groups typically establish the procedures and guidelines to support product safety (including product advertising and warning), gather insight from prior product defects for evaluation, and oversee regulatory reporting. However, while a committee may be effective for large established companies, it may be more challenging for smaller merchants and manufacturers with more limited human resources.

(2) Contractual mechanisms – Companies can limit product liability risks through contractual mechanisms with appropriately limited warranties and disclaimers. In the US, an example would be to limit warranties to those expressly provided under Section 2-313 Uniform Commercial Code (UCC) . Additionally, product contracts can be subject to appropriate remedy limitations, such as under Section 2-719 UCC. This allows the manufacture to, for instance, limit or exclude remedies for consequential damage. However, there are often statutory restrictions against contract terms that limit remedies for consumers. Moreover, while contractual mechanisms may help to mitigate legal liability, it is less effective in preserving customer relationships and corporate goodwill. Being subject to a contentious product liability claim will inevitably damage the companies’ reputation, regardless of the consequences of litigation.

(3) Audit programs – Audit programmes can help to identify potential defects before customer injuries occur, and also identify products that have been subject to warranty claims before a legal claim arises. Audit programs can be complimentary to having a product safety committee, to encourage ongoing compliance with product safety regulations and also address product defects early before becoming defect claims. However, significant time and human capital will be required to conduct a comprehensive audit, which entails detecting potential defects out of potentially thousands of product purchases.

(4) Insurance – Most businesses invest in general liability insurance, product liability insurance and product recall insurance to mitigate against compensation payments required upon establishing product liability. However, whilst insurance offers additional protection when facing product liability lawsuits, product liability claims will increase insurance premiums in the long term. This has indeed been the trend, where net product liability insurance premiums increased from $2.3 million in 2011 to $3.2 million in 2020 in the US.

The above methods have been commonly adopted by companies to mitigate and product liability, but each contains its limitations. More effective mitigation can be achieved by harnessing information that is near real-time and can be accessed by both large and smaller companies alike, which brings us to customer engagement and feedback.The Harvard Business Review demonstrates an example where one customer provided a 10 out of 10 in CSAT score.However, the feedback included a comment stating, “The only thing that we were a bit disappointed with is to do with repairs…The fitters seem to be struggling with diagnosing the issue and it always seems to be more expensive.”

With NLP, keywords and topics from the comment can be extracted. Specifically, “fitters”is classified under resources, “diagnosing the issue” is grouped under activities, “a bit disappointed” is considered as a negative emotion,  and “struggling,” “more expensive,” is categorised under complaints. Taken together, AI tools can more easily help businesses identify irregularities in customer feedback from digital platforms. This is conducive to issuing early warnings of potential product liability that the company may have previously overlooked. The ability to capture a customer’s emotional and cognitive responses with near real-time analytics can therefore equip a company to prioritise actions that will improve the customer experience. Combined with human intelligence, more proactive actions can be taken before a product issue escalates into a lawsuit.


In line with the growth of e-commerce and increasingly plaintiff-friendly regulatory attitudes, adopting a proactive approach to minimise product legal liability becomes imperative for a business’s financial health and reputation. The analysis of customer feedback data using AI offers an opportunity for companies to effectively monitor consumer feedback, to identify and remedy any product issues before they escalate into legal claims. This data source can be complimentary to existing strategies in place to mitigate product liability claims, including product safety committees, contract provisions, audit programs, and insurance. Importantly, the early prevention of product liability disputes allows a business to maintain its reputation and trust with its current and future customers.

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