Abstract:
On one hand, product innovation is essential for businesses to compete in dynamic markets, such as the eyewear industry, a continually evolving sector where technological advancements play a strategic role in shaping its best practices.
Product innovation was, in fact, one of the top three strategic priorities for 71% of businesses, according to the Boston Consulting Group Senior Executive Innovation Survey. Additionally, 70% of businesses regarded newly developed products as "important" or "very important" to their future.
On the other hand, nowadays Artificial Intelligence (AI) is confirmed to have become a disruptive force in Product Development, by redesigning the process from ideation to market penetration and imposing its pivotal role across almost all stages of the product lifecycle.
Indeed, AI impacts the ideation phase, where it augments creativity through advanced algorithms and data-driven insights; the designing phase, where it transforms user experience and usability, leveraging natural language processing, computer vision, and recommendation systems to personalize product interfaces and to analyse diverse user preferences; the prototyping phase, where it facilitates rapid iteration and refinement by leveraging machine learning algorithms; and the testing phase, where it optimizes reliability, performance, and scalability, thus mitigating risks associated with product failure and enhancing overall product quality.
The ambition of this elaborate is to understand to which extent embracing AI's innovative opportunities can support companies in navigating unpredictable markets' landscapes while also driving sustainable growth and competitive advantages, as well as to identify the best practices or managerial strategies for leveraging these innovations effectively from a corporate perspective.
In fact, the interdisciplinary nature of the topic provides an opportunity not only to get insights from diverse fields and broaden their understanding, but also allows to gain a deeper understanding and practical knowledge of the eyewear industry, including its challenges, opportunities, and emerging trends, fostered by personal interests and passion for a sector able to merge aesthetic, creativity, and innovation into high-quality, functional, as well as timeless, products.
Therefore, the study offers an initial exploration of the current landscape of technological innovations that can find a useful application in Product Development processes in this industry, by analysing their effects not only on traditional processes but also on the evolution of the industry.
As far as structure is concerned, the thesis begins with an analysis of the current academic literature on Product Development best practices, providing an overview of the most common strategies employed by companies.
This preliminary investigation is followed by a detailed presentation of interested AI-powered technologies, particularly Generative AI and Machine Learning, focusing on their features, advantages, and relevance to Product Development activities.
The final section of the thesis consists in an empirical analysis based on a selected case study, that explores the practical applications of these AI technologies within the development of EssilorLuxottica’s eyewear products.
Lastly, as technologies in the AI domain continue to advance rapidly, this research aims at envisioning a potential future of their further improvement by thoroughly analysing the correlation between technological innovation and possible implications and needs related to Product Development processes in the eyewear industry.