The Behavioural Economics of AI Driven Personalisation by Aarvee Mishra

The Behavioural Economics of AI Driven Personalisation by Aarvee Mishra

Introduction

Behavioural economics was introduced in the 20th century, but has taken a different form in the modern world. According to Capgemini, over 70% of consumers expect personalised interactions and report that AI helps them make faster decisions. Here is an example to better understand the utility of AI in economics:The famous beauty brand Sephora has developed its app with features such as virtual,real-time product try-ons, skin and foundation analysis, and more. In this case, as in many others, AI-driven personalisation increased engagement and sales. I always enjoy finding things on the Sephora app or just visiting it. However, finding LEGO on Amazon can be confusing. I am both a LEGO enthusiast and a make-up enthusiast. So, is it possible that consumers get overwhelmed by too many choices suitable for them? AI is meant to simplify decisions for consumers, but it can alsocomplicate them. This paradox between feeling seen and feeling overwhelmed is one I aim to dissect through my research

For consumers, it is beneficial to understand the underlying psychology of giving in to AI-driven results to avoid making irrational decisions. Businesses use personal data to curate outputs, yet very few people are aware of how much of their data they give away. According to the World Economic Forum, 75% of business leaders believe that AI personalisation will give them a competitive edge, yet only 7% include AI in major decisions. The question is: to what extent are we willing to compromise their privacy for optimal decision-making experiences? Will our experiences genuinely be maximised, or will they result in choice overload? We can anticipate future studies based on the long- term impacts of AI-personalisation on markets.

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