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Quick Read: Product Development & Artificial Intelligence

 

 

How Can Artificial Intelligence be Involved in Product Development?  

 

Let’s focus on two main ways that AI can help with Product Development. Firstly, AI can do the repetitive and boring tasks or jobs in this industry that us humans don’t usually enjoy. Secondly, AI can gather the best information relevant to the product development so that better quality products can be produced.  

  

Testing Product Features 

The shortage of quality assurance engineers and analysts in the workplace means that the quality standard of products is not always up to scratch. Testing the features of products can make up 50% of the work being done on a product before it is even approved for production. This is seen as a huge timeconsumer – especially when aspects such as customer and competitor research are being overlooked. 

An AI automated approach can help in this regard. By assimilating, machines can meticulously mimic human behaviour. This means that a team of testers can move beyond the traditional route of manually testing products and progressively move forward toward an automated and precision-based continuous testing process. AI models can test the features of the product to find faults (with a higher chance of finding faults that a human product manager may have missed). Not only are product faults lessened by using AI models, but human error is minimised too. Even the most meticulous tester is bound to make mistakes while carrying out monotonous manual testing. By performing the same steps accurately every time, AI models never miss out on recording detailed results. Testers are freed from repetitive manual tests and have more time to create new automated software tests and deal with sophisticated features. 

 

Designing for Ultimate User Experience 

Successful products are generally those with uses that resonate with the users. The product needs to be user-friendly and, in some cases, even fun to use. Product design calls for creativity across the board. The design team must consider the product uses (regular and unusual) and support those uses that embrace the business objectives as well as those that give the user value.  

 Artificial Intelligence can use behavioural data to determine how a product is used and how it can be built to best fulfil its use. The most useful part of this determination is that AI can alert the design team before the manufacturing phase as to which designs will and what won’t be successful. By analysing the intended steps to use a product, AI can determine whether a user will be successful in getting the desired action from the product or not. This means that it is no longer necessary to build different prototypes of a product for testing. Simply run all the different product designs through a simulation and let AI models determine which is best. This is ground-breaking for companies that are heavily reliant on manufacturing: saving them time and money previously spent on product development and research. 

 

 

As Artificial Intelligence has become relevant in the product development cycle, organizations are faced with the decision whether they should adopt it wholly within their practices. Initially, the set-up costs of an AI system may seem unjustifiable in the product development industry, but in time organisations will produce greater testing rewards for less money.  These new savings can be redirected towards quality assurance efforts, testing uncovered areas, or more exciting and creative parts of product testing. In the future, AI in product development won’t only be relevant in product testing but will be applicable to all roles across product development involved in delivering top-quality products to the market. 

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