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AI Use Cases

A collection of over 250 uses for artificial intelligence

A continually updated list exploring how different types of AI are used across various industries and AI disciplines,including generative AI use cases, banking AI use cases, AI use cases in healthcare, AI use cases in government, AI use cases in insurance, and more

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Product customisation

Introduction

The retail industry has always been a pioneer in the implementation of technologies that help to improve the quality of service for customers, reduce costs and boost revenues. Another great example of the recent developments is the use of Generative AI or Gen AI in the area of product customization. While Narrow AI has a limited ability to solve specific tasks, Gen AI has the capability of understanding, learning and applying knowledge to different tasks, which makes it even more valuable in the diverse world of retail. It enables the retailers to provide their customers with products that are tailored to their wants and needs, thus improving the customers’ satisfaction and retention.

Challenges

There are however some challenges that retailers face in the implementation of Gen AI in product customization. The first challenge is the implementation of the AI technology into the current systems which may be quite complex and expensive to implement. Also, the retail industry is known to handle a large volume of data which makes it difficult to organize and analyze. There is also the issue of data privacy and security since AI applications usually need some sensitive information of the customers. Also, there is a problem of scalability since the solutions must be able to cater for the large number of customization requests that are made in real time. Lastly, some of the retailers may have little knowledge and perception about AI technology hence becoming a barrier to its adoption.

AI Solutions

Here’s how Gen AI can address some of these challenges. In the area of data management and analysis, AI can help in organizing large amounts of data and recognizing the similarities and differences that can be applied to help with the product customization process. Also, there is the use of machine learning algorithms that can be used to enhance such processes with each iteration. In data privacy and security, AI systems can be developed with strong encryption and privacy protocols to safeguard sensitive data. In the area of scalability, the AI systems can be developed in a way that they can accommodate a large number of customization requests in real-time and have the capacity to increase or decrease the processing power depending on the demand. To counter the lack of understanding and skepticism about AI, there is a need to create awareness and provide education to the retailers on the advantages and possibilities of AI in the retail sector.

Benefits

There are numerous advantages of using Gen AI in product customization in the retail sector. For the customers, it can enhance the experience to the extent of buying products that are tailored to their wants and desires. For retailers, it can result to better customer relations and hence increased customer retention and sales. It also means that the process will be more efficient and effective thus increasing profitability. In addition, AI can also help to decrease the time and costs required for product customization thus enabling other aspects of the business to be well attended to. In addition, AI can also offer important knowledge regarding customer’s behavior and preferences that could be further applied in creating new products as well as marketing strategies.

Return on Investment

It is possible to realize a high ROI when implementing Gen AI in the process of product customization. A recent McKinsey report indicates that AI has the capability of contributing to the global GDP by $13 trillion by 2030 which means an additional 1.2% GDP growth annually. In the retail industry alone, AI can enhance profitability by 60%, as stated by Capgemini. These numbers are quite impressive and indicate that the funding of AI can be very fruitful.

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