Essay on Adoption of Artificial Intelligence and Related Technologies in Education and E-Commerce Industry Sectors

Executive summary

Artificial Intelligence (AI) technologies have been highly adopted by many industries globally. Two of the leading industries to adopt these technologies are the education and e-commerce industries. Research on the education sector shows that 1 in 10 learning institutions have deployed and invested in AI. 1 in 5 are conducting a pilot, and only 1 in 3 lack plans in Artificial Intelligence. Similarly, a study on the e-commerce sector in 2019 shows that the number of businesses adopting AI grew by 270% in four years, with most of the growth occurring between 2018 and 2019. Also, statistics indicate that 9 in 10 leading businesses have an ongoing investment in AI. This paper aims to discuss the adoption of AI and related technologies in the education and e-commerce industry sectors. The paper discusses the factors that influence the adoption and implantation of AI in both industries. The need for personalization, tutoring, and providing education access to students with special needs are factors that influenced adoption in the education sector. Similarly, the e-commerce industry has needed to personalize its customer needs and build a robust inventory management system. There have been different kinds of AI technologies adopted by these sectors, such the Big data, chatbots, and robotics.

The paper uses education journals articles to look at the benefits both the education and e-commerce sectors encounter. Task automation, saving time, personalized tutoring, efficient sales, and dynamic pricing are some of the benefits discussed. Additionally, the paper compares the benefits and outcomes in the two industry sectors. Moreover, just like any other technology, adopting these technologies in the industries has had its challenges. The education sector has reported high costs of bridging the digital gap, ethics, and data transparency issues. Also, e-commerce has experienced human capital gaps and challenges in data collection. Further, for better adoption and implementation of these AI technologies, the paper recommends hiring data scientists and planning an AI budget for its businesses.

1.0 Introduction

Artificial Intelligence is the simulation of human intelligence demonstrated by machines. Typically, AI-powered machines have an intelligent entity that gives them the capability of performing tasks intelligently without being explicitly instructed (Carroll 2020). Currently, AI is the big talk in all technological conversations. It lives within everyone’s daily lives, surrounded by the use of the internet and mobile devices. Similarly, businesses and governments have increased their use of AI techniques and tools to improve business processes and solve recurrent business issues. The adoption of these tools and techniques has brought about exciting realities that have never been experienced in human social life. These forms of reality have resulted in individuals spending a considerable amount of time on social media platforms and various technological environments for social and professional reasons.

The interactivity of AI technologies is majorly on the internet. This interactivity has evolved in broad dimensions of mobility and intelligence. With technological advancements in internet speeds and connection capacity, networked digital solutions have moved to the cloud. On the question of intelligence, AI’s concern is more on simulating intelligent behaviors or tasks that are observable in plants, animals, and the human world. As a result, robots have emerged and can perform activities such as grasping an object and moving it to another position. A chatbot is another example of an intelligent technology that has the capability of conversing with consumers through their natural language and assist them in making a good decision such as that in purchasing products.

Another technology that relates to the AI field is augmented intelligence. It involves achieving human and machine collaboration through synergistic intelligence. This is significant, especially for digitally supported businesses and life events, as it creates room for improving both machine intelligence and human intelligence through both human and machine support. It is mainly used as a decision support system. For example, in the e-commerce sector, augmented intelligence has been used to provide statistics for the number of customers who abandon their carts and analyze the data to get their reasons. It offers solutions capable of optimizing the e-commerce store to reduce the abandonment of shopping carts.

Moreover, there have been emerging automation technologies relating to the field of AI. Automation technologies are involved where digital interactions are faced with dealing with a large amount of structured and unstructured data. This has led to the development of tools and techniqu