The Behavioural Impact of Artificial Intelligence: Theory of Consumption Value Perspective

Introduction

Artificial Intelligence (AI) is a crucial general-purpose technology, the machine’s ability to continuously improve its performance without requiring humans to explain precisely how to complete all tasks assigned to it (Brynjolfsson & Mcafee, 2017). Numerous AI-enabled systems have been created since 1956 when the word “Artificial Intelligence” first appeared. In recent years, AI has been significantly more effective and widely accessible. Current AI technologies like natural language processing, machine learning, data mining, genetic algorithms, and expert systems are being applied in an astounding range of fields. AI is expected to permeate most industries, contributing approximately USD 15.7 trillion to the global economy by 2030 (Murphy et al., 2021). The advancement of technology in health care (early detection), education (customised teaching aids), customer service (voice assistants, chatbots), and transportation (self-driving vehicles) improves humans’ everyday lives (Becker, 2019; Kashive et al., 2020; Kaye et al., 2020; Murphy et al., 2021).

AI is typically present from the moment individuals wake up, as smart devices use AI to optimise daily rituals, ranging from recommending personalised news updates to changing room temperatures (Ashimova, 2020). For instance, without AI, search engines like Google could not provide what individuals want from a search of the entire Internet. AI powers the advertisements that appear to follow a person, tailored to them based on their search history, and designed to provide outcomes that the algorithms think the person will find valuable. In the workplace, AI automates procedures and augments decision-making, resulting in enhanced efficiency and productivity (Zhang et al., 2021). Moreover, AI contributes to diagnosis and treatment plans in healthcare, improving the precision of medical care (Pan et al., 2019). In some cases, once algorithms outperform humans, they will likely quit completing tasks themselves. For instance, instead of writing responses to emails, individuals use Smart Replies in Gmail (McIlroy-Young et al., 2020). As a result, humans are increasingly coming into interaction with AI tools.

Individuals in today’s world prioritise convenience and reducing time and effort in doing a task. AI has enhanced the convenience and efficiency of individuals by reducing human-dependence (van Esch et al., 2021). Therefore, individuals are increasingly adopting AI tools because of the transformative benefits these tools provide in their daily lives. The understanding of the value of AI and the beneficial effects it can have on numerous facets of human living is critical to its mainstream adoption. A significant behavioural change happens as individuals discover the convenience and efficiency provided by AI-powered solutions. Furthermore, as individuals’ trust in AI-powered applications grows, it also increases their willingness to rely on those applications and accept AI-driven recommendations, resulting in behavioural changes (Glikson & Woolley, 2020).

However, the need for an appropriate awareness of AI prevents individuals from accepting and understanding the actual value of AI. AI acceptance is sometimes an instinctive response, like using AI chatbots pretending as non-AI agents. For instance, an online banking AI chatbot can appear as a customer care representative, giving the consumer the impression that they are speaking with a human rather than an AI chatbot (Kelly et al., 2023). Therefore, to understand the real value of AI and accept AI applications, individuals should be aware of where AI is utilised and its industries, contexts, and AI application types. The main focus of this study is to understand how human behaviour has changed with the context, industry, and application type of AI and to understand the future use of AI. The contributions of this study are twofold: How consumption values affect the behavioural intention to use AI with different contributions and how trust and frequency of use affect the relationship between consumption values and behavioural intention to use AI.